Build Your Own Radar System
Scarito, Michael
Radar is used extensively by the military, police, weather, air travel, and maritime industries - why not you? Come learn how to build a radar imaging system on the cheap! This talk will explain the basics of how radar works as well as how to measure range and velocity of your chosen targets. You will learn how to use synthetic aperture techniques to generate a two- or even three-dimensional image. The hardware and software design will be totally opened up so you can go home and build your own system. The talk will try to run through the basics pretty fast, so some knowledge of electronics or basic physics might help, but is not required! Regardless of your background, you will see the capabilities of a modern home-built radar system and hopefully get some ideas for your own uses. Michael Scarito is a multidisciplinary hacker masquerading as an electrical engineer. Interests include physical and cyber security, surveillance systems, innovative uses for radio frequency electronics, and projects which incorporate all of the above.
 Okay. Hi everyone. My name is Michael Scurrito and I'm going to talk to you about how you can build your own radar system. So this talk is a little bit off the wall, I guess. You know, traditionally it's more security focused at DEF CON, but I thought it was a pretty cool topic and I like remote sensing systems, so I wanted to present something that I've been working on with some people at MIT. So when talking about stuff like this, there's going to be some amount of math. I mean, there's not really any way to avoid that, so I do apologize in advance, but you know, we're going to talk about it and hopefully I'll explain it in a way that you can understand pretty easily. But I didn't want to, you know, kind of overwhelm anyone with it, so I'll try my best. I agree. So first of all, what is radar? Basically, it's some way of looking at the world through radio waves. You know, you're measuring something, you're sensing some sort of electromagnetic field and basically what you're doing generally is you send out a pulse and you look at the response. So radar used to be an acronym, it's become a word, it stands for radio detection and ranging and that's basically what it is. So, you know, what you might think of traditionally is something like, you know, these, I think that's a weather radar from like the 40s or something. So, you know, that's kind of the basic idea of what people think, but we can, what you're measuring is essentially position of something, velocity of something, direction of motion of something. But the thing is you can actually do a lot with this type of technology. You can look at pretty much anything. I mean, you can look at like here we've got people, you can look at terrain like land surface, you can look at, you know, foliage, weather patterns, you can look at clouds, rain, ships, aircraft, spacecraft, like pretty much anything you can think of. So, I'm not really talking about something like this, but what we can do today is more something like this. This is an image of the capital. I guess this is a Sandia radar system, but this is what synthetic aperture radar can really do with a nice system. So what we have is a 3D point cloud of the capital building taken from an aircraft. So, you know, why do it yourself? Why is this, you know, something that we could talk about now? And the reason that, you know, it's particularly interesting nowadays is because it's become extremely easy to do this and it's become cheaper than it ever was before to do this. And the big thing was the wireless revolution has given us access to a lot of hardware that used to be really expensive and pretty much only available to the military, but the need for it in the commercial communication space means you can buy a lot of this stuff just off the shelf. And the other thing is for processing, all this stuff used to be done in analog. Nowadays, you can just feed it into a computer and the computer will do pretty much everything for you. And I guess, you know, the main reason to do it yourself is because it's pretty cool. You can do some pretty interesting things with it. You know, the stuff that I'm going to demonstrate today, hopefully, is not even close to the extent of what you can do. I just want to give a simple demo of, like, you know, in this space, what can we look at? So who am I? I'm from MIT. I'm an electrical engineer, mostly, and the rest of the time I do pretty much anything else engineering or science related when I need to. Currently, I'm working on RF remote sensing systems, not radar systems, but actually weather instrumentation at MIT. And I have a pretty broad set of interests, but a lot of stuff related to RF technology, including RFID, communication stuff, imaging systems, remote sensing, wireless comm, and, you know, security, of course, is a big interest of mine. And anything that can combine those issues is awesome. So I guess what I'm going to start with is talking about how radar works in a general sense. Then I'm going to go a little more detail, like, how would you actually make some of these measurements I was talking about with the radar system? After that, you know, talk about how you could build your own radar. Hopefully, we can demo it if it works for me. I'm going to go into a little more about synthetic aperture radar, which is basically a technique for taking pictures with radar. And this is both 2D and 3D imaging. And then we'll go into maybe improving the design of the home-built radar, like, what sort of stuff I'm looking to do in the future and what stuff I'd love to see some people here talking about next year if they did it themselves. So first with an overview. Like I said before, the basic idea is, you know, we transmit a signal and we get some kind of return off of it. So, you know, this is an aviation system. So basically what this is doing is it's spinning around, sending out a pulse and measuring how long it takes to come back. But it's not necessarily that specific. You could do a lot of processing with that return signal. And the key point here is that every radar system works on this type of principle. You're transmitting a signal from somewhere or somebody is transmitting a signal from somewhere and you're looking at how that reflects off of a target. And all this is governed by this thing called the radar equation, which is this big thing with a whole bunch of terms that, you know, there's a whole bunch of stuff here. So basically what we're looking at is the function of received power versus transmitted power. And the way that that gets changed is, you know, you get transmitter gain, antenna aperture, which is like how big your dish is, cross-section, propagation factor refers to the medium that you're in. I actually don't really care about most of this stuff right now. The main point I want to make is this target distance here. So we have power over r to the fourth. That means that basically, you know, your transmit power doesn't matter that much. So the received power is going to decrease with the fourth power of the distance. So if you move by a factor of 10 away, like, you know, I guess my example here is if you receive a signal of one milliwatt at 10 meters at a kilometer, that's 10 picawatts. It's really fucking tiny. So, you know, but that sounds kind of bad because it does severely limit your range. But at the same time, the system right here that I'm going to show uses about 10 milliwatts of transmit power. That's only 10 times worse than 100 watt radar, which would be like the size of a car. So you really, you can get a lot of performance with kind of these low cost, like, simple systems. So where's radar used in general? It's pretty much used for anything. I'll go over a couple applications. Air traffic control is a really big one. They use it for in-route tracking. So this is actually a picture from a website you can go to to like track flights live. It's kind of neat. So this is Las Vegas a couple days ago. It's used for weather measurement. It's a huge set of data for trying to track precipitation. So what's happening here is this is this is a Doppler radar image. So what it's doing is it's actually measuring the velocity of the rain or the hail or whatever it's looking at. And the color is the strength of the return. So it's how much precipitation is there. But the other cool thing is they can figure out which way the storm's moving by the Doppler shift or the signal, which is why it's called Doppler radar. Another thing is, you know, police applications. They use speed guns to, you know, give you tickets and that sucks. But, you know, it's a lot of uses. On the automotive side, there's actually a lot more of this stuff. So anytime you want to kind of track things that are close by, there's radar systems there. Also, LiDAR, to some extent, which is pretty similar. But they're using it for cruise control now so your car can follow a certain distance behind the next car. Collision avoidance, your car will pie the brakes right before you hit something. Automated parking, which I think is in the Prius, uses radar to figure out where the parking spot is. And then, you know, autonomous vehicles in general are going to need a ton of this technology to figure out where they are in like the near space. It's used for surveying applications. So you can fly a plane over some terrain and get a 3D image of what the train looks like. That's pretty useful. And the military uses it for practically everything. They love radar. You know, it's hard to get some good examples, but, you know, pretty much any system that involves, you know, shooting something somewhere or like looking at something or, you know, anything that they might want to do is going to use some sort of radar system. And like I said, it's kind of hard to get good examples. So why radio frequency? You know, you can, there's tons of sensing systems that operate from, you know, basically extremely low frequency, maybe like tens of kilohertz, even lower, like tens of hertz, all the way up to visible light beyond like X-rays and everything up there. So, you know, what's special about this frequency band? And by the way, what we're talking about is something in the range of 50 megahertz to about 50 gigahertz. So, and more recently, we've been going up from there. But what's special about this range is we get pretty good propagation in the atmosphere. So we can transmit a signal that runs thousands of miles or thousands of kilometers. And it can go through the atmosphere, through space, not so much through water because it's hard to propagate through that. And that's why we have a seminar. But the signals are, you know, they can travel through clouds or smoke obscuration. To some extent, with certain systems, you can penetrate the ground. And there's something called ground penetrating radar for searching for tunnels or wiring or anything under there without actually digging it up. The signals travel really fast. Which is both a positive and a negative. So the plus side is, well, you know, it's, you're getting your signal there really fast. You can detect things really far away in a short amount of time. Like Sonar could take minutes to go any real distance. But, you know, this is, oh, this is instantaneous. 300,000 kilometers a second, I think is like six or seven trips around the world in a second. And the other advantage is that the antennas are reasonably sized. So we used to use systems that were lower frequency, hundreds of megahertz, tens of megahertz. And anyone that does amateur radio knows how freaking big those antennas are. And if you want a directional antenna, it's going to be even bigger. Because that dish is going to be 50 meters, 100 meters. That is enormous. So we can build stuff with like, you know, a can. This is at 2.4 gigahertz. This can is what, three inches in diameter. And it's coffee can. So, you know, how do we build these radio frequency systems? The big thing is that it's hard to build circuits that operate at these frequencies. If you think about your computer and how hard it is to get the CPU to run it, you know, four gigahertz or something, that is a chip that's about, you know, three quarters of an inch on the side. It's trying to switch at that frequency and get a signal three quarters of an inch or less. And that's at four gigahertz. If we want to build something that's like a transmitter at 50 gigahertz, that's going to be really hard to like do any sort of complex digital coding or modulation or anything like that. So the way that virtually every single radio works is what they do is they process the data at some low frequency. So like, if you have a, you know, a voice like FM radio or something, the transmitter is just recording audio and it's processing audio. And then when it gets ready to transmit, it just magically shifts that signal to the frequency it's transmitting at, up to, you know, 100 megahertz or something. And what this is called is heterodining. Radar pretty much works the exact same way in almost every case. So the way this works is there's a little more and more math here. So the trig identity that I'm looking at is the product of some role. Basically, if you multiply two trig functions or two sine waves at two different frequencies, what you get out is the sum of the, there's some, the frequency of their sum and the difference of the two frequencies. And you lose half the power basically in the process of doing that because the two signals are, you know, half. So what this is called is mixing. So what we're getting, you know, the sum in different, different frequencies. So as an example, if you take your 2.4 gigahertz like Wi-Fi signal and you mix that with something that's very slightly higher, this is 2.400001 gigahertz, then you get something at about 4.8 gigahertz, which you don't really care about because, well, I don't know, I don't really need it. And you get something at 1 kilohertz, which is actually a lot more interesting. So I can measure very precisely what the frequency of that second signal is if I'm very good at measuring the first one because they're really close to each other. And, you know, I can get this 1 kilohertz like resolution, for instance. That's pretty useful. So there's a device called a mixer, which basically multiplies some known signal with your unknown signal and it shifts it in frequency. And that's just magical. You can do, that's how radio is possible. So as a visual example of this, we take two functions, which I just got an octave. You know, we have sine of t, sine of 1.1 times t. So that's something that's like 10 percent faster in frequency. If you multiply those, you get something like this. This is, what you can see here is the sum of two signals. One of them is a fast moving signal and the other one is a slow moving signal. So, you know, looking at in the frequency domain, it's the same sort of thing. And this is actually a relevant picture. So if you haven't done some stuff like this before, it could be a little bit foreign to you. But basically what we're looking at with these arrows is that's indicating that there's a continuous wave tone. That's the sine wave at that frequency. And it has no energy in any other frequency. So that sine wave in time is equivalent to that spike or delta in frequency. So in this third example, what you get out is these two different frequencies. And as an example of this, you've probably heard this before. If you have a bunch of like case fans in a computer, for instance, you can get those really annoying like very time varying tones. So if you have something running like 6,000 RPM and one running at like 6,010 RPM, you have a 10 RPM signal that's being generated acoustically between those two things. So you have some faster signal and then you have this slower one. And that's going to give you that like beating tone, which is really annoying. That's exactly what's happening there. So let's talk a little bit more about what we can measure here. So like I said before, there's a couple things that we're talking about. Direction is like, if I have some target, which, where do I go to get to it? Range is the distance to the target. And velocity is kind of how fast the target is moving. So then we can combine all these things into basically imaging. So we can use various techniques to generate a 2D or a 3D picture, which is what I'm calling this range and cross range domain of one of these measurements. And when I say range and cross range, what I mean is in the radar world, if you take a picture of like this wall, for instance, or that wall, whatever, your two dimensions are kind of like up and to the side. They're both perpendicular to you. The radar kind of flips that 90 degrees. So one of your dimensions is range, which is like how far away the thing is. And the other one is like in some other axis. So it's cool because you can look from the side and then get like kind of an overhead view of what something looks like. So if we want to measure range, it seems pretty simple, right? We send out a pulse, you know, just hang it out and wait for the response. And we just time how long that takes. So here's a visual depiction here. If we have a transmit pulse at time zero, then, you know, we're going to get some returns from some targets. And we're going to say one is like, I don't know, 15 meters away. One is 30 meters. One is 65. And so that seems pretty easy. We just look for them like a scope or something. And the reason that this is hard is because the waves travel really fast. They travel at the speed of light. So we have this equation. The time it takes to get back is two times the distance because it has to go there and come back divided by the speed of light, which means that at 70 meters, we're talking about, I guess, that's 500 nanoseconds of time, which is pretty hard to measure if you want to do it easily. So if you're using a sound card, for instance, which is what the original version of this thing actually used to sample, that 44 kilohertz sample rate corresponds to a 7 kilometer distance in space and range. So, you know, that's probably not going to work for most systems. So if we're trying to measure velocity now, and I'm going to go back to range in a second, let's say we want to measure a person walking. Well, they move really slow. So it's going to be kind of hard to, like, see a real change, right? So the way this is done is with the Doppler effect. If we have something moving, like this is, I guess, the car analogy, you know, we have a car driving by on the road and you're standing there on the side of the road and you're listening to it. When it's coming towards you, you know, it sounds a little bit higher pitched. It passes you and the frequency suddenly drops and it sounds lower pitched. And that's because any, like, sound being generated by the car is basically being, like, compressed in space as it propagates because the car is moving as those waves are coming, you know, emanating from the car. So it's a higher frequency tone and it's a lower frequency tone. So if we send a radar pulse, like, what I'm calling a continuous wave tone, which is just a sine wave, at something that's moving towards you, it's going, when it reflects that, it's going to increase the frequency because it's moving faster. It's not going to change the propagation speed because everything moves at the speed of light, you know, due to relativity. But it's going to compress it in time, or in space, rather, so it's going to increase the frequency of the signal. So, you know, if we had a three meters per second signal, we're turning that 2.4 gigahertz into 2.4 plus 24 hertz. So that's going to be pretty hard to differentiate. But if we have a really good 2.4 gigahertz reference, we can just mix with that and we get out 24 hertz. And I can see that on a scope pretty easily. I can measure that. And then that way I know pretty accurately how far away the target is. And by the way, the previous example was kind of how radar first got developed. It was, that's like basically a pulse radar. This would be called continuous wave operation, which basically means you're transmitting one frequency all the time. So, going back to measuring range, if we're trying to see a difference in frequency, it's pretty easy. We can do that. And the really cool thing is if you take that into the computer and Fourier transform it, you can very easily get a plot of the frequency at, you know, versus power. And it's harder to see a difference in time just because we can't sample that fast or it's expensive to sample that fast. So, what if we took the frequency that we're transmitting that we're, you know, we have plotted here and we just ramp it? So, what that means is it's going to be a tone that looks sort of like this. It's, this is called a chirp. And what's happening is, you know, it starts out at a low frequency and it just gets faster and faster and faster and then it's done. And then it restarts or goes back down or something. So, what happens with the return signal then if you're trying to transmit it at something that's far away is, you know, you get, like, let's say the first line is a transmitted signal and the second line is the received signal. So, you have, if you're looking at what you're transmitting at a given time compared to what you just received, it's going to be shifted by however much time it took between, you know, when you sent it and when you just got it back. And so, that's some small amount of time. But if you're ramping the frequency, it actually corresponds to a difference in frequency. And then you can actually do the exact same thing. If you mix those two signals together using a mixer, you will get out basically the difference in frequency between the two signals. And what that means, you know, practically is, let's say we have a 10 meter target or, you know, something that's 10 meters away. If we ramp over 200 megahertz in 20 milliseconds, which is reasonable, you know, it's something that we can achieve pretty easily, that, you know, point, whatever the hell that is, I don't know how long that is. But I think it's 66 nanoseconds or something. That signal turns into 667 hertz, which is in the middle of the audio range. I could sample that with a sound card and tell you how far away you are. So, this is known as FMCW radar, Frequency Modulated Continuous Wave. And that's how I think most of the systems work today. So then, you know, let's say we want to go a little bit further and then we want to take a picture of something. So, there's a few ways of doing that. But basically, at a high level, what we're doing is we're basically just taking these measurements and just repeating them again and again and again in some different place or different orientation or whatever. So, there's a few ways of doing that. One is just scanning. So, if you've ever seen a big dish just spinning around repeatedly, you'll probably seen them at airports before. All that's doing is it's a very directional beam and it's just pointing it out and measuring the responses back to try to find all the planes. And so, it just scans and it, you know, just traces out a path. And it's exactly what you see on those old radarscopes where you have a line going around your little circular screen. So, you know, we've gotten a little bit more sophisticated in that sense then. So, there's something called synthetic aperture radar which basically means you can get better resolution if you have a bigger dish. But the problem is then you have a bigger dish. And the bigger dishes are more directional, so that's the advantage. So, with synthetic aperture radar, what you're doing is you're actually taking coherent measurements of the signal at different places and you're trying to simulate having a larger dish. And, you know, the reason you would do that is so that you can get a finer resolution of space. So, if you just point it in one direction, like, I think the beam was on these things were like 40 degrees or something. So, you couldn't see shit out there. But the idea is that you make it highly directional by simulating measurements from multiple places and then you can kind of combine all those measurements together and get a, you know, range cross range plot. And I can't do that live right now, but I will show you some pictures of that. And then, you know, another system is actually called Inverse SAR where you actually, you keep the radar fixed, but you move the target. And this is if you want to get like kind of radar cross-section measurements of an aircraft or something. I'm not sure why you'd want to do that. But, you know, yeah. And then more recently, something that they've been doing is called, it's basically multi-antena beamforming. And beamforming is where you take a whole bunch of antennas and you, instead of having like a directional beam to begin with, you basically steer the beam with the antennas. And the way that works is you're basically adjusting the phase of each signal so that you have some flat front in some direction. And you can control that direction and scan really fast. And the advantage there is you have no moving parts and you can scan really, really quickly. And we use, you know, we use that for a bunch of surveillance applications. Like it's just, it's useful if you want to find things really fast. And it's much more flexible than something that just physically scans. So, you know, let's go on to, you know, how you might build a system like this. So, I, the home-built radar that I have here, which I guess if you want to get a good look at it, I guess come to the Q&A room and we can show it off. The original design was by this guy named Greg Charvet. He's an employee at MIT and, you know, I've worked with him a good bit and he's a pretty cool guy. So, he's, he really loves radar. And so he designed this system to be built as an MIT class, as basically a, I think it's a two-week long class where you just learn how to build these things. And it's, it's pretty simple. The cost is a few hundred dollars. It operates in the Wi-Fi band, 2.4 gigahertz. And it's, it's pretty simple to use. The downside, at least with the one that I built, is that it's actually really hard to get through airport security. They give you a lot of shit if you try to take something like that on the plane. What I, what I was told when I went through the check-in was that, well, I, I, I showed, I flagged the guy down and I showed him this thing and he's like, what the hell's that? And I tell him it's a radar and he's like, what's that? So, so, you know, I was like, okay, you can look in here or something. And then, you know, his comment was perfect. He's just, he just says, it looks like a bomb. And I was like, well, I'm glad I didn't say that. But anyway, eventually they did let me through and I was able to get here. Hopefully I'm not on a watch list now. So, let's try to, let's try to describe how the system works. So, this is a, this is a block diagram for RF stuff. And I guess it's, that's not too hard to read up here. So, this is how RF engineers kind of like deal with the world of circuit. So, we know, this isn't really a circuit. It's a set of components. So, you know, I'll try to go through it and explain what's happening here. So, the first thing is, the thing that says modular, that little like spike thing is, that's the ramp generator. It's generating just a ramp and voltage, which gets fed to this thing with the curvy line called a voltage controlled oscillator. And it does exactly what you think. The frequency of oscillation is related to the input voltage. So, you send it a ramp and it gets faster and faster. And that generates the chirp I was talking about earlier. There's an attenuator, a power amplifier, which just makes the signal, you know, louder, more powerful. That signal gets split. And one of the, you know, one of the copies of the signal gets transmitted out by, you know, one of these, one of these dishes here, coffee cans, sorry. The other one, the other part of the signal goes to that mixer. And that's what I said before, was the local oscillator for that mixer. So, then what happens is the signal gets sent out by one antenna. It gets reflected off of whatever. And then it comes back and the other antenna gets amplified again because it's going to be really, really weak. Now, remember that one over R to the fourth thing I was talking about. And then it gets mixed with that known signal. So, then it basically, what we did is we took a signal and we shifted it all the way down to pretty low frequency near DC where we could record it. With the original system for this, used the sound card. I've actually changed that a little bit since then. But that's what's cool about this, is you can literally build something like this and record your radar data with your sound card. And just process it on the computer with, you know, you record with audacity and then process it in MATLAB. That was how the original system worked. And then there's this thing down here called a video amplifier. And what that does is it basically just takes that really small signal that's still pretty small and amplifies it a bunch of times at low frequency so we can feed it out to the computer. And there's two outputs to this. One of these is the sync pulse which basically tells us when the chirp starts and then the other one is the actual data signal back out. And then I guess the components are here. You can get those slides later. But these are all off the shelf parts from this company called Mini Circuits which builds these things. They basically, they take a little chip and they put it in the package and do all the testing to make it actually work. And then you just like screw on little SMA connectors to it. It's pretty cool because you just, it's like doing plumbing but you're building an RF circuit. So here's a picture of the thing that's sitting right there. I guess, I think I have call outs on the next page. So basically these are all the parts I just talked about. It's a little bit different than that diagram because that green board is not in the original design. That's actually basically a USB data acquisition board that I developed for this. And I'm working on getting that to be releasable but right now it's not quite ready for public use yet. But eventually I'd like to just kind of publish the designs online. So you can see all the components I was talking about before. We have, you know, the VCL first which gets a signal from that green board which is actually generating our ramp now. So it's computer controlled. So the VCL goes to the attenuator, goes to one of those amplifiers and then you see the splitter out there. One of those signals goes to the transmit can antenna which you can see at the bottom. And then, you know, the other signal goes to the mixer. The received signal goes to one of the other amplifiers into the mixer and then everything goes out to the video amplifier and then back into the board. So that's basically, you know, that's pretty much all the components we just talked about. I guess just for completeness I'm not going to explain these schematics but this is the original circuit. This is something you could build yourself really easily to do data capture. So one of these things is the video amplifier, that thing at the, you know, the box thing at the top. And the other one is the ramp generator which is just a chip that generates ramps. And it generates two output signals which you plug into your sound card and record your radar data. Yeah? Sorry? Yeah. Oh, so the reason that's there is because when I was trying to make this in USB powered and so I just wired it onto the power for this other stuff. Everything on here runs off of 5 volts. So I plug the USB in and then the computer doesn't like that. It just turns off the port. So the problem was the interest current was too high and I needed something to like slow that down. So I was like, okay, I'll put an inductor in there. And the only thing I could find was this big like choke transformer thing. So I just shoved that in there and that worked. So that's all that's for. Okay, so let's say we want to do a little bit more. We want to get a little more sophisticated in the sound card because there are some disadvantages there. It's hard to collect every chirp. It's hard to stay synchronized and it's not as fast as we might like for sample rate. So I developed this board that's basically a microcontroller with an A to D, D to A converter. The way that we generate the ramp is we take a digital signal in the D to A converter and then feed it through an integrator. And if you remember your signals and systems, that continuous line turns into a ramp and we can control the speed of that ramp. And the reason that we're not just directly generating the ramp is because if you ever looked at how a DAC outputs a signal, every time you switch it, it like jumps to the next level a little bit. It doesn't like kind of smooth it out. So we could filter the hell out of it and it probably wouldn't work or we could just do something like this where we just generate a flat signal and then in analog we make the ramp. And that was the easiest option and it works pretty well. And then we just send that out to the VCO. And then on the receive side, you know, we have a video amp that was actually not on the green board, sorry, on the other board there. And then there's an A to D converter which is way faster than the other one. I think you could actually run it 500,000 samples per second, which is a lot faster than your sound card at 44, 96 or something like that if you have a nicer one. And the other advantages are, you know, internal triggering which basically means I start the ramp and I know where the ramp is and then I start to capture at a certain point. I capture data really fast and then it's done and I send it back to the computer. So it's completely kind of self-contained. I don't have to deal with like processing it later to do the triggering. And that makes a lot of the real time stuff a lot easier. So this is a picture of the board. I guess there's not really too much to say here. It's just, you know, yay circuits. And then there's a call outs on that. So actually the two other things on there that I didn't mention was the gyro and accelerometer. And I haven't really gotten to using these yet, but this is part of my future plan is, well, if we can just track the position of the thing, we can do a lot of this kind of coherent imaging stuff without any effort. And I'll talk about that a little more later. So I'd like to try a demo now. I really hope this works, but, you know, I'm not, I know how demos work at DEF CON tonight. I'm not, you know, we'll see what happens. But basically what we're going to do is we're going to try to do a range finding demo. So I'm going to take this thing and set it up to basically generate a chart, record the response and display it on the screen. And what's going to happen is there'll be a couple of plots there and I'll describe those when they come up. But basically what you should be able to see is the distance to a wall or something is going to come up as a stronger signal at some range. And we'll plot it with respect to range. And then all that processing is done with an FFT. So let's see if I can get out of this. Okay. Oh, wow. That worked surprisingly well. So if I plug this under the computer. So we have to hope that VM or properly captures the device because sometimes it doesn't like to. Let's just confirm that. It looks like it's connected. So a little Python program. I actually found this program online. It was just like something to generate an audio spectrum. And I was like, well, it's Python. It's going to be really easy to make it do whatever the hell I want. So I adapted it to my little USB serial interface. And actually I should probably, I think I'm forgetting something. I got to set the mode on this. Sorry. Whatever. Let's see if this works. So it doesn't give any error messages. We should be getting something scrolling across the screen in a second. Oh, okay. So there's a couple different things here. So in the middle plot, there's actually a lot of noise here. And I can explain why that probably isn't a little bit. So that plot in the middle is basically the time plot of the signal that we're sending out. Or this is the response. So this is literally at low frequency. It's basically an audio tone is what it would sound like. And that's related to the signal. It's not very directly related. So what we do is we Fourier transform that, which you can see on the left and the right. So the one on the right is kind of a scrolling view of that. And it's kind of hard to see the scale on here. But on that spectrogram view, those numbers are supposed to be the distance in meters to whatever you're looking at. So I guess you've seen a fish finder before. It's basically the same interface. So what I can do is I point it at the wall. I'm pretty sure that that strong response at about 30 meters is probably about the distance to that, which sounds about right. I point it up at the ceiling. It's going to drop down. And we see a very strong red line at about eight. You know, it's about the correct distance. And we can just kind of scan it around. You know, so, sorry? Yeah. So we get something at about four, which is, right. So, you know, it's basically, you can also see the power thing here. So when this is being displayed, this is a log scale. So it's not going to decline as fast as you would expect. But as they get further out, obviously the signal gets way, way weaker. And the other thing, which I haven't actually seen yet, which I'm a little surprised by, is so this thing operates in the Wi-Fi band. There's a lot of noise. I'm not exactly sure why that's happening. That was happening before. But what you do see occasionally is these pulses kind of towards the top end of that. And that's actually Wi-Fi signal bursts from the thing transmitting. It's a, you know, I think it's a 20 megahertz wide signal. And what you see that for is like a little pulse in the middle of the time window. And unfortunately, I guess no one's using Wi-Fi devices in here because I'm not picking anything up. So I guess everyone's being smart now and they're not using Wi-Fi at DEF CON. But yeah, I mean, this is basically, you know, that's all there is to it to doing something, you know, pretty simple. So literally all I did here is I'm recording the analog signal. I'm 4A transforming it and displaying it on the screen. And that's all there is to it. So let's go, let's go there. So let's head back to the talk. I'm glad that worked. So let's talk a little bit about, you know, trying to image with one of these things. So synthetic aperture radar is basically the idea of instead of having, you know, a really big antenna or a lot of little antennas, let's just take this thing and like move it, like slide it down a table or something and just keep taking images. And there's two basically techniques of doing that. One is basically kind of scanning around the object that you want to look at and it's called spotlight SAR as you might expect. The other option is basically trying to scan your radar across a scene and getting, you know, basically getting these repeating pulses to the side. And that's actually, it's a little easier to process. So that's how this was originally working. And I'll give you an example of that in a second. Basically what you're doing is you take these pulses and you can get a lot of information about the phase of that signal. So that analog signal that I showed you in the time domain is actually pretty important because all the phase of those frequencies affects like subtly the difference between, you know, your transmitter and various elements of the target. So you can kind of coherently combine those and get a 2D image. So this is an example that Dr. Charvet gave me of what he built with something that's very similar to this using the same sort of specifications. So we have a 2D image from Google Earth and he went out to this field and he did this. I think, I mean, you know, you move the, basically you move the radar about eight feet and you get an overlay image like this. So I'm going to go back and forth a couple of times. But what's cool is you're basically looking at the foliage from the tree. So you get all those red areas are basically where there's something that return. And the other thing is you can see that telephone pole or whatever the hell that is right there is also giving a pretty strong return. And the range on this is like a couple of hundred feet. So it's actually pretty good. I was testing this in my car at one point and I was actually able to get about probably about half a kilometer. If you're going down the highway and you see like some faraway objects, you can kind of see them like getting closer to you as you move. So that's kind of neat. So let's talk about what you might be able to do to improve on this sort of stuff. One thing was what I was talking about before. I'd really like to do an inertial star system. And unfortunately I've been having some problems with the accuracy of the accelerometer in gyro. I'm going to be working on that in the near future to try to get that accurate enough for my purposes so I can do position tracking for basically a few seconds enough to capture the image. And so what we would do is we basically use a gyro and accelerometer to figure out relative position and orientation as I move the thing around. And the idea is that I don't have to measure that. I don't have to like, you know, carefully annotate what I'm doing as I'm capturing the data. It makes it much faster. And a cool thing you might be able to do is if you take a GPS and a magnetometer, you probably could just georeference it on a map, have the direction you're looking and just overlay it on, you know, a Google Earth map. And at this point you can pretty much do that with a smartphone because that's got all of those sensors. Just add that with a sensor like this and you're good to go. You just got to write threats off of. The other thing is something that we might actually be doing at MIT in the next few months is a phase array radar system. So what we would do there is we'd have a set of transmit and receive antennas. And the system here is we basically switch between pairs of them. So you might have, you know, a couple of transmit antennas, a couple of receive antennas. Each pair of those, if they're spaced appropriately, basically gives you a virtual antenna at a different position. And so you can just very rapidly switch between, you know, let's say you have like eight on each side, that's 64 different pairs of antennas or 32. Anyway, whatever. You get, I think it's 64, yeah. I get 64 pairs of like virtual antennas that you can take and you can very quickly generate an image. And I guess, so basically what we would get with that is, I have a video here of something that's actually been built. This was built by MIT. This is a, what is the video? Okay. What they did here is they built a phase array radar system designed to capture images at 10 hertz. And what's happening here is they have a metal ball in the middle. And then what they did is they rolled another metal ball past it. And you can basically see the thing rolling in real time past the thing. And it's pretty neat. So you see that little dot there, it just kind of comes past. And so this is pretty fast. There's another video online which I couldn't include due to time. There's someone like swinging a baton. And it's interesting because like I said before, this is an overhead view. So if someone's swinging that, it looks like a spike and then it kind of spreads out and goes back and forth and back and forth. So, you know, that's, I can play that again. But yeah, you can see right there, it just kind of comes by. And then there's a little bit of interference when it comes past it due to multi-path effects of the signal. Because remember, we are looking at electromagnetic waves here. But this is the sort of capability you could, you know, achieve with something, you know, a little more sophisticated because the real-time aspect is really interesting. And real-time imaging, I think, would be pretty cool to implement, especially as like a do-it-yourself thing. So I have a few more references here. I guess you can get these from the slides. But these are some resources. This is probably enough information to build one of these things. Maybe not with the laser cut stuff. But it's, you know, it's not that hard. I mean, it's a pretty simple concept. And all the parts are available commercially nowadays, which is amazing. So I guess, you know, the main reason I gave this talk is because I really wanted to see people build something like this, you know, actually build it. And so that's kind of like my call to action. It's like, I would love to see someone do something really cool with this stuff and come back next year and, you know, say, okay, I'm going to give a talk on, you know, my, you know, improvements to the system. That would be awesome. So I think that's about all I have. So yeah, I guess if there's any questions, you know, go ahead. Yeah. Sorry. I can't hear you. Oh, well, the coffee cans are somewhat directional. Sorry, he asked why coffee cans is opposed to a different type of antenna. The coffee cans are fairly directional. They are really cheap because they're coffee cans and we had them anyway. But basically it's going to be hard to see inside this thing. So you might just have to come back later and see. But what the way this works is there's an SMA connector in here and there's a little wire being fed into here. So this is basically a wave guide port. It's an adapter from that little feed antenna to this larger wave guide. And then that just, it's basically a crappy directional antenna. But you could use another for Wi-Fi, so if you wanted to make your signal more directional, it's the exact same principle. And if you took some of those really big Wi-Fi antennas, you could make a highly directional system just with that. So anyone else? Yeah, he asked which microcontroller I'm using. I'm actually using a pick. It's one of the 16-bit picks. I tend to get a lot of shit for using their parts, but in general what I find is that they're very inexpensive. I love that. They're very cheap parts. And this thing was like two bucks and has off the shelf USB and stuff. So it's pretty good for my applications. Oh, yeah, that's worth talking about. So, yes, for the power requirements work. I believe this entire system uses about 200 milliamps at 5 volts. So like I said, it's easily powered by the USB port. It's the only power source here. The original one was powered off of two sets of AA batteries. So that's about all you're talking about. Yeah. Okay, so this system is operating in the Wi-Fi... Oh, sorry, I've got to do this. He asked how much could I increase the power. The limits at 2.4 GHz, I believe, are a watt. But that's a watt. I think it's 4 watts radiated. So you could transmit. What's that? Okay. So you could basically... You probably had to transmit a watt and no one's going to complain too much. The problem with this is you would have to band limit it some more. So the way this works is it does actually extend past the Wi-Fi band a little bit. And that's why we only use it in controlled environments. But basically, we don't want to step on anyone else's spectrum. So I wouldn't transmit a watt in that whole range. This is like 10 milliwatts. It's pretty low. So, yeah. Anyone else? Yeah. Well, okay. What's the signal to noise with Wi-Fi? So I guess it's pretty dual because what you see is actually with the Wi-Fi signals, you actually see the burst on the spectrum. I'm actually... I was shocked. I didn't see that today. I was sure someone was going to be using Wi-Fi device in here. But basically what happens is you get these little blips in the signal. And that chirp is like fucked. It's a pretty strong signal. And it's hard to filter out because it's not related to your signal at all. You're just like basically sweeping right through it and you pick up all that crap. But if they're not transmitting, it's not really a big deal. Yeah. Is the upper frequency limit defined by how easily you can obtain a reference signal? Is the upper frequency limit defined by how easily you can obtain a reference signal? The frequency bands that you can operate in are... It's mostly... I mean, there's a few bands you can operate in. You pretty much are stuck to the ISM bands if you want to do this stuff legitimately because those are what's licensed for this unrestricted or pseudo unrestricted use. So if you go up to 5 gigahertz, it would be a little harder to find parts. Basically as you go up in frequency, the parts just get a little more expensive. Or as you get even higher, they can get a lot more expensive. But the big thing you want actually in a system like this is you want wide bandwidth because the bandwidth is what's giving you that spatial resolution and the time resolution. Anyone else? Yeah. He asked if I was looking at software to find radio systems. I think there would be some benefit to that if you wanted to make, you know, do some... Certainly the SAR coherent processing stuff, that would benefit greatly from an FPGA system because it does... It can take a few seconds to process an image like that on the computer. But in this case, like the main goal is simplicity and low cost. So, you know, if you bring in, you know, one of those... What is it? Edis Research Board's and like the USRP or something, that's going to add a big chunk of change to your design. But there's definitely a lot of potential there. I would say that's absolutely worth exploring. Anyone else? Yeah. Yes, is the Doppler effect from a fast-moving object enough to mess up your position measurement? That kind of depends on what you're trying to do. Okay. So, I guess if it's... If you're trying to measure something moving really fast, like on the order of, you know, like a plane or something, you might have some impact. So, I guess when I was talking about it before, I said that something was moving three meters per second, which is like a person walking really quickly or maybe slow jog, is producing a 24 hertz signal. At the chirp rates I was dealing with, you know, I think 10 meters corresponded to like 667 hertz. So, it wouldn't affect it too much. But that all depends on your chirp rate and your bandwidth and, you know, a bunch of other factors. So, yeah. You could make it have an impact or not. And the other thing is there's actually a way of disambiguating those. Because I didn't talk about this, but you can chirp up and you can chirp back down. And if you think about it, the effects are a little bit different because the Doppler shift is always going to change the frequency in one direction. But if you chirp the other direction, it will shift it backwards. So, all you have to do is kind of figure out what's happening there and you can disambiguate them. Is that it? Oh, got one more. Okay. Should I keep doing questions or? Okay. Yeah, go ahead. Yeah. On that microcontroller, it would be pretty hard. The processing power on this thing is pretty weak. It's just, it's useful for fastly grabbing, or quickly grabbing data. If you switch to like a DSP or like, you know, an ice arm or an FPGA would be, you know, probably the best option in that regard. You could definitely do that. It's not, it's not a very computationally intensive process. I mean, this is like a Python script I was running to do the FFT. Oh, okay. Yeah, yeah. So, to some extent, actually, for the SAR stuff, we want something a little less directional than that. Part of it is that the COGICANs were what was available at the time. But, no, what? That's probably true. Yes. But, yeah, I mean, it's pretty open. You basically get different characteristics. So, if you're trying to do the SAR imaging, having a wide beam width is actually somewhat useful because you can get, it decreases some of your spatial fidelity, but you also get a wider image. So, if you have a very narrow beam, you're not going to get any signal from something that's, you know, further apart. So, it's a trade-off there. Anyone else? Okay. I guess if there's anyone else that wants to, like, see the system closer or talk, I think I'm going to move over to the Q&A room. So, yeah, thanks for, thanks for hearing my talk. That's great.
 Okay. Hi everyone. My name is Michael Scurrito and I'm going to talk to you about how you  can build your own radar system. So this talk is a little bit off the wall, I guess. You  know, traditionally it's more security focused at DEF CON, but I thought it was a pretty  cool topic and I like remote sensing systems, so I wanted to present something that I've  been working on with some people at MIT. So when talking about stuff like this, there's  going to be some amount of math. I mean, there's not really any way to avoid that, so I do  apologize in advance, but you know, we're going to talk about it and hopefully I'll explain  it in a way that you can understand pretty easily. But I didn't want to, you know, kind  of overwhelm anyone with it, so I'll try my best. I agree. So first of all, what is radar?  Basically, it's some way of looking at the world through radio waves. You know, you're  measuring something, you're sensing some sort of electromagnetic field and basically what  you're doing generally is you send out a pulse and you look at the response. So radar used  to be an acronym, it's become a word, it stands for radio detection and ranging and  that's basically what it is. So, you know, what you might think of traditionally is something  like, you know, these, I think that's a weather radar from like the 40s or something. So,  you know, that's kind of the basic idea of what people think, but we can, what you're  measuring is essentially position of something, velocity of something, direction of motion  of something. But the thing is you can actually do a lot with this type of technology. You  can look at pretty much anything. I mean, you can look at like here we've got people,  you can look at terrain like land surface, you can look at, you know, foliage, weather  patterns, you can look at clouds, rain, ships, aircraft, spacecraft, like pretty much anything  you can think of. So, I'm not really talking about something like this, but what we can  do today is more something like this. This is an image of the capital. I guess this is  a Sandia radar system, but this is what synthetic aperture radar can really do with a nice system.  So what we have is a 3D point cloud of the capital building taken from an aircraft. So,  you know, why do it yourself? Why is this, you know, something that we could talk about  now? And the reason that, you know, it's particularly interesting nowadays is because it's become  extremely easy to do this and it's become cheaper than it ever was before to do this.  And the big thing was the wireless revolution has given us access to a lot of hardware that  used to be really expensive and pretty much only available to the military, but the need  for it in the commercial communication space means you can buy a lot of this stuff just  off the shelf. And the other thing is for processing, all this stuff used to be done  in analog. Nowadays, you can just feed it into a computer and the computer will do pretty  much everything for you. And I guess, you know, the main reason to do it yourself is  because it's pretty cool. You can do some pretty interesting things with it. You know,  the stuff that I'm going to demonstrate today, hopefully, is not even close to the extent  of what you can do. I just want to give a simple demo of, like, you know, in this space,  what can we look at? So who am I? I'm from MIT. I'm an electrical engineer, mostly,  and the rest of the time I do pretty much anything else engineering or science related  when I need to. Currently, I'm working on RF remote sensing systems, not radar systems,  but actually weather instrumentation at MIT. And I have a pretty broad set of interests,  but a lot of stuff related to RF technology, including RFID, communication stuff, imaging  systems, remote sensing, wireless comm, and, you know, security, of course, is a big interest  of mine. And anything that can combine those issues is awesome. So I guess what I'm going  to start with is talking about how radar works in a general sense. Then I'm going to go a  little more detail, like, how would you actually make some of these measurements I was talking  about with the radar system? After that, you know, talk about how you could build your  own radar. Hopefully, we can demo it if it works for me. I'm going to go into a little  more about synthetic aperture radar, which is basically a technique for taking pictures  with radar. And this is both 2D and 3D imaging. And then we'll go into maybe improving the  design of the home-built radar, like, what sort of stuff I'm looking to do in the future  and what stuff I'd love to see some people here talking about next year if they did it  themselves. So first with an overview. Like I said before, the basic idea is, you know,  we transmit a signal and we get some kind of return off of it. So, you know, this is  an aviation system. So basically what this is doing is it's spinning around, sending  out a pulse and measuring how long it takes to come back. But it's not necessarily that  specific. You could do a lot of processing with that return signal. And the key point  here is that every radar system works on this type of principle. You're transmitting  a signal from somewhere or somebody is transmitting a signal from somewhere and you're looking  at how that reflects off of a target. And all this is governed by this thing called the  radar equation, which is this big thing with a whole bunch of terms that, you know, there's  a whole bunch of stuff here. So basically what we're looking at is the function of received  power versus transmitted power. And the way that that gets changed is, you know, you  get transmitter gain, antenna aperture, which is like how big your dish is, cross-section,  propagation factor refers to the medium that you're in. I actually don't really care about  most of this stuff right now. The main point I want to make is this target distance here.  So we have power over r to the fourth. That means that basically, you know, your transmit  power doesn't matter that much. So the received power is going to decrease with the fourth  power of the distance. So if you move by a factor of 10 away, like, you know, I guess  my example here is if you receive a signal of one milliwatt at 10 meters at a kilometer,  that's 10 picawatts. It's really fucking tiny. So, you know, but that sounds kind of bad  because it does severely limit your range. But at the same time, the system right here  that I'm going to show uses about 10 milliwatts of transmit power. That's only 10 times worse  than 100 watt radar, which would be like the size of a car. So you really, you can get a  lot of performance with kind of these low cost, like, simple systems. So where's radar  used in general? It's pretty much used for anything. I'll go over a couple applications.  Air traffic control is a really big one. They use it for in-route tracking. So this is actually  a picture from a website you can go to to like track flights live. It's kind of neat. So this  is Las Vegas a couple days ago. It's used for weather measurement. It's a huge set of data  for trying to track precipitation. So what's happening here is this is this is a Doppler  radar image. So what it's doing is it's actually measuring the velocity of the rain or the  hail or whatever it's looking at. And the color is the strength of the return. So it's  how much precipitation is there. But the other cool thing is they can figure out which way  the storm's moving by the Doppler shift or the signal, which is why it's called Doppler  radar. Another thing is, you know, police applications. They use speed guns to, you  know, give you tickets and that sucks. But, you know, it's a lot of uses. On the automotive  side, there's actually a lot more of this stuff. So anytime you want to kind of track  things that are close by, there's radar systems there. Also, LiDAR, to some extent, which  is pretty similar. But they're using it for cruise control now so your car can follow a  certain distance behind the next car. Collision avoidance, your car will pie the brakes right  before you hit something. Automated parking, which I think is in the Prius, uses radar  to figure out where the parking spot is. And then, you know, autonomous vehicles in general  are going to need a ton of this technology to figure out where they are in like the near  space. It's used for surveying applications. So you can fly a plane over some terrain and  get a 3D image of what the train looks like. That's pretty useful. And the military uses  it for practically everything. They love radar. You know, it's hard to get some good examples,  but, you know, pretty much any system that involves, you know, shooting something somewhere  or like looking at something or, you know, anything that they might want to do is going  to use some sort of radar system. And like I said, it's kind of hard to get good examples.  So why radio frequency? You know, you can, there's tons of sensing systems that operate  from, you know, basically extremely low frequency, maybe like tens of kilohertz, even lower,  like tens of hertz, all the way up to visible light beyond like X-rays and everything up  there. So, you know, what's special about this frequency band? And by the way, what  we're talking about is something in the range of 50 megahertz to about 50 gigahertz. So,  and more recently, we've been going up from there. But what's special about this range  is we get pretty good propagation in the atmosphere. So we can transmit a signal that  runs thousands of miles or thousands of kilometers. And it can go through the atmosphere, through  space, not so much through water because it's hard to propagate through that. And that's  why we have a seminar. But the signals are, you know, they can travel through clouds or  smoke obscuration. To some extent, with certain systems, you can penetrate the ground. And  there's something called ground penetrating radar for searching for tunnels or wiring  or anything under there without actually digging it up. The signals travel really fast.  Which is both a positive and a negative. So the plus side is, well, you know, it's, you're  getting your signal there really fast. You can detect things really far away in a short  amount of time. Like Sonar could take minutes to go any real distance. But, you know, this  is, oh, this is instantaneous. 300,000 kilometers a second, I think is like six or seven trips  around the world in a second. And the other advantage is that the antennas are reasonably  sized. So we used to use systems that were lower frequency, hundreds of megahertz, tens  of megahertz. And anyone that does amateur radio knows how freaking big those antennas  are. And if you want a directional antenna, it's going to be even bigger. Because that  dish is going to be 50 meters, 100 meters. That is enormous. So we can build stuff with  like, you know, a can. This is at 2.4 gigahertz. This can is what, three inches in diameter.  And it's coffee can. So, you know, how do we build these radio frequency systems? The  big thing is that it's hard to build circuits that operate at these frequencies. If you  think about your computer and how hard it is to get the CPU to run it, you know, four  gigahertz or something, that is a chip that's about, you know, three quarters of an inch  on the side. It's trying to switch at that frequency and get a signal three quarters  of an inch or less. And that's at four gigahertz. If we want to build something that's like  a transmitter at 50 gigahertz, that's going to be really hard to like do any sort of complex  digital coding or modulation or anything like that. So the way that virtually every single  radio works is what they do is they process the data at some low frequency. So like, if  you have a, you know, a voice like FM radio or something, the transmitter is just recording  audio and it's processing audio. And then when it gets ready to transmit, it just magically  shifts that signal to the frequency it's transmitting at, up to, you know, 100 megahertz or something.  And what this is called is heterodining. Radar pretty much works the exact same way in almost  every case. So the way this works is there's a little more and more math here. So the trig  identity that I'm looking at is the product of some role. Basically, if you multiply two  trig functions or two sine waves at two different frequencies, what you get out is the sum of  the, there's some, the frequency of their sum and the difference of the two frequencies.  And you lose half the power basically in the process of doing that because the two signals  are, you know, half. So what this is called is mixing. So what we're getting, you know,  the sum in different, different frequencies. So as an example, if you take your 2.4 gigahertz  like Wi-Fi signal and you mix that with something that's very slightly higher, this is 2.400001  gigahertz, then you get something at about 4.8 gigahertz, which you don't really care  about because, well, I don't know, I don't really need it. And you get something at 1  kilohertz, which is actually a lot more interesting. So I can measure very precisely what the frequency  of that second signal is if I'm very good at measuring the first one because they're  really close to each other. And, you know, I can get this 1 kilohertz like resolution,  for instance. That's pretty useful. So there's a device called a mixer, which basically multiplies  some known signal with your unknown signal and it shifts it in frequency. And that's  just magical. You can do, that's how radio is possible. So as a visual example of this,  we take two functions, which I just got an octave. You know, we have sine of t, sine  of 1.1 times t. So that's something that's like 10 percent faster in frequency. If you  multiply those, you get something like this. This is, what you can see here is the sum  of two signals. One of them is a fast moving signal and the other one is a slow moving  signal. So, you know, looking at in the frequency domain, it's the same sort of thing. And this  is actually a relevant picture. So if you haven't done some stuff like this before, it  could be a little bit foreign to you. But basically what we're looking at with these  arrows is that's indicating that there's a continuous wave tone. That's the sine wave  at that frequency. And it has no energy in any other frequency. So that sine wave in  time is equivalent to that spike or delta in frequency. So in this third example, what  you get out is these two different frequencies. And as an example of this, you've probably  heard this before. If you have a bunch of like case fans in a computer, for instance,  you can get those really annoying like very time varying tones. So if you have something  running like 6,000 RPM and one running at like 6,010 RPM, you have a 10 RPM signal that's  being generated acoustically between those two things. So you have some faster signal  and then you have this slower one. And that's going to give you that like beating tone,  which is really annoying. That's exactly what's happening there.  So let's talk a little bit more about what we can measure here. So like I said before,  there's a couple things that we're talking about. Direction is like, if I have some target,  which, where do I go to get to it? Range is the distance to the target. And velocity is  kind of how fast the target is moving. So then we can combine all these things into basically  imaging. So we can use various techniques to generate a 2D or a 3D picture, which is  what I'm calling this range and cross range domain of one of these measurements. And when  I say range and cross range, what I mean is in the radar world, if you take a picture  of like this wall, for instance, or that wall, whatever, your two dimensions are kind of  like up and to the side. They're both perpendicular to you. The radar kind of flips that 90 degrees.  So one of your dimensions is range, which is like how far away the thing is. And the  other one is like in some other axis. So it's cool because you can look from the side and  then get like kind of an overhead view of what something looks like.  So if we want to measure range, it seems pretty simple, right? We send out a pulse, you know,  just hang it out and wait for the response. And we just time how long that takes. So here's  a visual depiction here. If we have a transmit pulse at time zero, then, you know, we're  going to get some returns from some targets. And we're going to say one is like, I don't  know, 15 meters away. One is 30 meters. One is 65. And so that seems pretty easy. We just  look for them like a scope or something. And the reason that this is hard is because the  waves travel really fast. They travel at the speed of light. So we have this equation.  The time it takes to get back is two times the distance because it has to go there and  come back divided by the speed of light, which means that at 70 meters, we're talking about,  I guess, that's 500 nanoseconds of time, which is pretty hard to measure if you want to do  it easily. So if you're using a sound card, for instance, which is what the original version  of this thing actually used to sample, that 44 kilohertz sample rate corresponds to a  7 kilometer distance in space and range. So, you know, that's probably not going to work  for most systems. So if we're trying to measure velocity now, and I'm going to go back to  range in a second, let's say we want to measure a person walking. Well, they move really slow.  So it's going to be kind of hard to, like, see a real change, right? So the way this  is done is with the Doppler effect. If we have something moving, like this is, I guess,  the car analogy, you know, we have a car driving by on the road and you're standing there on  the side of the road and you're listening to it. When it's coming towards you, you know,  it sounds a little bit higher pitched. It passes you and the frequency suddenly drops  and it sounds lower pitched. And that's because any, like, sound being generated by the car  is basically being, like, compressed in space as it propagates because the car is moving  as those waves are coming, you know, emanating from the car. So it's a higher frequency tone  and it's a lower frequency tone. So if we send a radar pulse, like, what I'm calling  a continuous wave tone, which is just a sine wave, at something that's moving towards you,  it's going, when it reflects that, it's going to increase the frequency because it's moving  faster. It's not going to change the propagation speed because everything moves at the speed  of light, you know, due to relativity. But it's going to compress it in time, or in space,  rather, so it's going to increase the frequency of the signal. So, you know, if we had a three  meters per second signal, we're turning that 2.4 gigahertz into 2.4 plus 24 hertz. So that's  going to be pretty hard to differentiate. But if we have a really good 2.4 gigahertz  reference, we can just mix with that and we get out 24 hertz. And I can see that on a  scope pretty easily. I can measure that. And then that way I know pretty accurately how  far away the target is. And by the way, the previous example was kind of how radar first  got developed. It was, that's like basically a pulse radar. This would be called continuous  wave operation, which basically means you're transmitting one frequency all the time. So,  going back to measuring range, if we're trying to see a difference in frequency, it's pretty  easy. We can do that. And the really cool thing is if you take that into the computer  and Fourier transform it, you can very easily get a plot of the frequency at, you know,  versus power. And it's harder to see a difference in time just because we can't sample that  fast or it's expensive to sample that fast. So, what if we took the frequency that we're  transmitting that we're, you know, we have plotted here and we just ramp it? So, what  that means is it's going to be a tone that looks sort of like this. It's, this is called  a chirp. And what's happening is, you know, it starts out at a low frequency and it just  gets faster and faster and faster and then it's done. And then it restarts or goes back  down or something. So, what happens with the return signal then if you're trying to transmit  it at something that's far away is, you know, you get, like, let's say the first line is  a transmitted signal and the second line is the received signal. So, you have, if you're  looking at what you're transmitting at a given time compared to what you just received, it's  going to be shifted by however much time it took between, you know, when you sent it and  when you just got it back. And so, that's some small amount of time. But if you're ramping  the frequency, it actually corresponds to a difference in frequency. And then you can  actually do the exact same thing. If you mix those two signals together using a mixer,  you will get out basically the difference in frequency between the two signals. And  what that means, you know, practically is, let's say we have a 10 meter target or, you  know, something that's 10 meters away. If we ramp over 200 megahertz in 20 milliseconds,  which is reasonable, you know, it's something that we can achieve pretty easily, that, you  know, point, whatever the hell that is, I don't know how long that is. But I think it's  66 nanoseconds or something. That signal turns into 667 hertz, which is in the middle of  the audio range. I could sample that with a sound card and tell you how far away you  are. So, this is known as FMCW radar, Frequency Modulated Continuous Wave. And that's how  I think most of the systems work today. So then, you know, let's say we want to go a  little bit further and then we want to take a picture of something. So, there's a few  ways of doing that. But basically, at a high level, what we're doing is we're basically  just taking these measurements and just repeating them again and again and again in some different  place or different orientation or whatever. So, there's a few ways of doing that. One  is just scanning. So, if you've ever seen a big dish just spinning around repeatedly,  you'll probably seen them at airports before. All that's doing is it's a very directional  beam and it's just pointing it out and measuring the responses back to try to find all the planes.  And so, it just scans and it, you know, just traces out a path. And it's exactly what you  see on those old radarscopes where you have a line going around your little circular screen.  So, you know, we've gotten a little bit more sophisticated in that sense then. So, there's  something called synthetic aperture radar which basically means you can get better resolution  if you have a bigger dish. But the problem is then you have a bigger dish. And the bigger  dishes are more directional, so that's the advantage. So, with synthetic aperture radar,  what you're doing is you're actually taking coherent measurements of the signal at different  places and you're trying to simulate having a larger dish. And, you know, the reason you  would do that is so that you can get a finer resolution of space. So, if you just point  it in one direction, like, I think the beam was on these things were like 40 degrees or  something. So, you couldn't see shit out there. But the idea is that you make it highly directional  by simulating measurements from multiple places and then you can kind of combine all those  measurements together and get a, you know, range cross range plot. And I can't do that  live right now, but I will show you some pictures of that. And then, you know, another system  is actually called Inverse SAR where you actually, you keep the radar fixed, but you move the  target. And this is if you want to get like kind of radar cross-section measurements of  an aircraft or something. I'm not sure why you'd want to do that. But, you know, yeah.  And then more recently, something that they've been doing is called, it's basically multi-antena  beamforming. And beamforming is where you take a whole bunch of antennas and you, instead  of having like a directional beam to begin with, you basically steer the beam with the  antennas. And the way that works is you're basically adjusting the phase of each signal  so that you have some flat front in some direction. And you can control that direction and scan  really fast. And the advantage there is you have no moving parts and you can scan really,  really quickly. And we use, you know, we use that for a bunch of surveillance applications.  Like it's just, it's useful if you want to find things really fast. And it's much more  flexible than something that just physically scans. So, you know, let's go on to, you know,  how you might build a system like this. So, I, the home-built radar that I have here,  which I guess if you want to get a good look at it, I guess come to the Q&A room and we  can show it off. The original design was by this guy named Greg Charvet. He's an employee  at MIT and, you know, I've worked with him a good bit and he's a pretty cool guy. So,  he's, he really loves radar. And so he designed this system to be built as an MIT class, as  basically a, I think it's a two-week long class where you just learn how to build these things.  And it's, it's pretty simple. The cost is a few hundred dollars. It operates in the Wi-Fi  band, 2.4 gigahertz. And it's, it's pretty simple to use. The downside, at least with the one that  I built, is that it's actually really hard to get through airport security. They give you a lot  of shit if you try to take something like that on the plane. What I, what I was told when I went  through the check-in was that, well, I, I, I showed, I flagged the guy down and I showed him  this thing and he's like, what the hell's that? And I tell him it's a radar and he's like, what's  that? So, so, you know, I was like, okay, you can look in here or something. And then, you know,  his comment was perfect. He's just, he just says, it looks like a bomb. And I was like, well, I'm  glad I didn't say that. But anyway, eventually they did let me through and I was able to get here.  Hopefully I'm not on a watch list now. So, let's try to, let's try to describe how the system  works. So, this is a, this is a block diagram for RF stuff. And I guess it's, that's not too hard to  read up here. So, this is how RF engineers kind of like deal with the world of circuit. So, we  know, this isn't really a circuit. It's a set of components. So, you know, I'll try to go through it  and explain what's happening here. So, the first thing is, the thing that says modular, that  little like spike thing is, that's the ramp generator. It's generating just a ramp and voltage,  which gets fed to this thing with the curvy line called a voltage controlled oscillator. And it  does exactly what you think. The frequency of oscillation is related to the input voltage. So,  you send it a ramp and it gets faster and faster. And that generates the chirp I was talking about  earlier. There's an attenuator, a power amplifier, which just makes the signal, you know, louder,  more powerful. That signal gets split. And one of the, you know, one of the copies of the signal  gets transmitted out by, you know, one of these, one of these dishes here, coffee cans, sorry. The  other one, the other part of the signal goes to that mixer. And that's what I said before, was the  local oscillator for that mixer. So, then what happens is the signal gets sent out by one  antenna. It gets reflected off of whatever. And then it comes back and the other antenna gets  amplified again because it's going to be really, really weak. Now, remember that one over R to the  fourth thing I was talking about. And then it gets mixed with that known signal. So, then it  basically, what we did is we took a signal and we shifted it all the way down to pretty low  frequency near DC where we could record it. With the original system for this, used the sound  card. I've actually changed that a little bit since then. But that's what's cool about this, is  you can literally build something like this and record your radar data with your sound card. And  just process it on the computer with, you know, you record with audacity and then process it in  MATLAB. That was how the original system worked. And then there's this thing down here called a  video amplifier. And what that does is it basically just takes that really small signal that's still  pretty small and amplifies it a bunch of times at low frequency so we can feed it out to the  computer. And there's two outputs to this. One of these is the sync pulse which basically tells  us when the chirp starts and then the other one is the actual data signal back out. And then I  guess the components are here. You can get those slides later. But these are all off the shelf  parts from this company called Mini Circuits which builds these things. They basically, they  take a little chip and they put it in the package and do all the testing to make it actually work.  And then you just like screw on little SMA connectors to it. It's pretty cool because you  just, it's like doing plumbing but you're building an RF circuit. So here's a picture of the  thing that's sitting right there. I guess, I think I have call outs on the next page. So  basically these are all the parts I just talked about. It's a little bit different than that  diagram because that green board is not in the original design. That's actually basically a USB  data acquisition board that I developed for this. And I'm working on getting that to be  releasable but right now it's not quite ready for public use yet. But eventually I'd like to just  kind of publish the designs online. So you can see all the components I was talking about before.  We have, you know, the VCL first which gets a signal from that green board which is actually  generating our ramp now. So it's computer controlled. So the VCL goes to the attenuator,  goes to one of those amplifiers and then you see the splitter out there. One of those signals goes  to the transmit can antenna which you can see at the bottom. And then, you know, the  other signal goes to the mixer. The received signal goes to one of the other amplifiers into  the mixer and then everything goes out to the video amplifier and then back into the board.  So that's basically, you know, that's pretty much all the components we just talked about.  I guess just for completeness I'm not going to explain these schematics but this is the original  circuit. This is something you could build yourself really easily to do data capture. So one of  these things is the video amplifier, that thing at the, you know, the box thing at the top. And  the other one is the ramp generator which is just a chip that generates ramps. And it generates two  output signals which you plug into your sound card and record your radar data. Yeah?  Sorry? Yeah. Oh, so the reason that's there is because when I was trying to make this in USB  powered and so I just wired it onto the power for this other stuff. Everything on here runs off  of 5 volts. So I plug the USB in and then the computer doesn't like that. It just turns off the  port. So the problem was the interest current was too high and I needed something to like slow  that down. So I was like, okay, I'll put an inductor in there. And the only thing I could find was  this big like choke transformer thing. So I just shoved that in there and that worked. So that's  all that's for. Okay, so let's say we want to do a little bit more. We want to get a little more  sophisticated in the sound card because there are some disadvantages there. It's hard to collect  every chirp. It's hard to stay synchronized and it's not as fast as we might like for sample  rate. So I developed this board that's basically a microcontroller with an A to D, D to A  converter. The way that we generate the ramp is we take a digital signal in the D to A converter  and then feed it through an integrator. And if you remember your signals and systems, that  continuous line turns into a ramp and we can control the speed of that ramp. And the reason that  we're not just directly generating the ramp is because if you ever looked at how a DAC outputs a  signal, every time you switch it, it like jumps to the next level a little bit. It doesn't like kind  of smooth it out. So we could filter the hell out of it and it probably wouldn't work or we could  just do something like this where we just generate a flat signal and then in analog we make the  ramp. And that was the easiest option and it works pretty well. And then we just send that out to  the VCO. And then on the receive side, you know, we have a video amp that was actually not on the  green board, sorry, on the other board there. And then there's an A to D converter which is way  faster than the other one. I think you could actually run it 500,000 samples per second, which is a  lot faster than your sound card at 44, 96 or something like that if you have a nicer one. And  the other advantages are, you know, internal triggering which basically means I start the ramp  and I know where the ramp is and then I start to capture at a certain point. I capture data  really fast and then it's done and I send it back to the computer. So it's completely kind of  self-contained. I don't have to deal with like processing it later to do the triggering. And  that makes a lot of the real time stuff a lot easier. So this is a picture of the board. I guess  there's not really too much to say here. It's just, you know, yay circuits. And then there's a  call outs on that. So actually the two other things on there that I didn't mention was the  gyro and accelerometer. And I haven't really gotten to using these yet, but this is part of my  future plan is, well, if we can just track the position of the thing, we can do a lot of this  kind of coherent imaging stuff without any effort. And I'll talk about that a little more  later. So I'd like to try a demo now. I really hope this works, but, you know, I'm not, I know how  demos work at DEF CON tonight. I'm not, you know, we'll see what happens. But basically what we're  going to do is we're going to try to do a range finding demo. So I'm going to take this thing and  set it up to basically generate a chart, record the response and display it on the screen. And  what's going to happen is there'll be a couple of plots there and I'll describe those when they  come up. But basically what you should be able to see is the distance to a wall or something is  going to come up as a stronger signal at some range. And we'll plot it with respect to range. And  then all that processing is done with an FFT. So let's see if I can get out of this. Okay. Oh, wow.  That worked surprisingly well. So if I plug this under the computer. So we have to hope that VM  or properly captures the device because sometimes it doesn't like to. Let's just confirm that. It  looks like it's connected. So a little Python program. I actually found this program online. It  was just like something to generate an audio spectrum. And I was like, well, it's Python. It's  going to be really easy to make it do whatever the hell I want. So I adapted it to my little USB  serial interface. And actually I should probably, I think I'm forgetting something. I got to set  the mode on this. Sorry. Whatever. Let's see if this works. So it doesn't give any error  messages. We should be getting something scrolling across the screen in a second. Oh, okay. So  there's a couple different things here. So in the middle plot, there's actually a lot of noise  here. And I can explain why that probably isn't a little bit. So that plot in the middle is  basically the time plot of the signal that we're sending out. Or this is the response. So this is  literally at low frequency. It's basically an audio tone is what it would sound like. And that's  related to the signal. It's not very directly related. So what we do is we Fourier transform  that, which you can see on the left and the right. So the one on the right is kind of a  scrolling view of that. And it's kind of hard to see the scale on here. But on that spectrogram  view, those numbers are supposed to be the distance in meters to whatever you're looking at. So I  guess you've seen a fish finder before. It's basically the same interface. So what I can do is  I point it at the wall. I'm pretty sure that that strong response at about 30 meters is probably  about the distance to that, which sounds about right. I point it up at the ceiling. It's going to  drop down. And we see a very strong red line at about eight. You know, it's about the correct  distance. And we can just kind of scan it around. You know, so, sorry? Yeah. So we get something  at about four, which is, right. So, you know, it's basically, you can also see the power thing  here. So when this is being displayed, this is a log scale. So it's not going to decline as fast as  you would expect. But as they get further out, obviously the signal gets way, way weaker. And  the other thing, which I haven't actually seen yet, which I'm a little surprised by, is so this  thing operates in the Wi-Fi band. There's a lot of noise. I'm not exactly sure why that's  happening. That was happening before. But what you do see occasionally is these pulses kind of  towards the top end of that. And that's actually Wi-Fi signal bursts from the thing  transmitting. It's a, you know, I think it's a 20 megahertz wide signal. And what you see that  for is like a little pulse in the middle of the time window. And unfortunately, I guess no one's  using Wi-Fi devices in here because I'm not picking anything up. So I guess everyone's being  smart now and they're not using Wi-Fi at DEF CON. But yeah, I mean, this is basically, you know,  that's all there is to it to doing something, you know, pretty simple. So literally all I did  here is I'm recording the analog signal. I'm 4A transforming it and displaying it on the screen.  And that's all there is to it. So let's go, let's go there. So let's head back to the talk.  I'm glad that worked. So let's talk a little bit about, you know, trying to image with one of  these things. So synthetic aperture radar is basically the idea of instead of having, you know,  a really big antenna or a lot of little antennas, let's just take this thing and like move it,  like slide it down a table or something and just keep taking images. And there's two basically  techniques of doing that. One is basically kind of scanning around the object that you want to  look at and it's called spotlight SAR as you might expect. The other option is basically trying to  scan your radar across a scene and getting, you know, basically getting these repeating pulses to  the side. And that's actually, it's a little easier to process. So that's how this was originally  working. And I'll give you an example of that in a second. Basically what you're doing is you take  these pulses and you can get a lot of information about the phase of that signal. So that analog  signal that I showed you in the time domain is actually pretty important because all the phase  of those frequencies affects like subtly the difference between, you know, your transmitter and  various elements of the target. So you can kind of coherently combine those and get a 2D image.  So this is an example that Dr. Charvet gave me of what he built with something that's very similar  to this using the same sort of specifications. So we have a 2D image from Google Earth and he  went out to this field and he did this. I think, I mean, you know, you move the, basically you move  the radar about eight feet and you get an overlay image like this. So I'm going to go back and  forth a couple of times. But what's cool is you're basically looking at the foliage from the tree.  So you get all those red areas are basically where there's something that return. And the other  thing is you can see that telephone pole or whatever the hell that is right there is also  giving a pretty strong return. And the range on this is like a couple of hundred feet. So it's  actually pretty good. I was testing this in my car at one point and I was actually able to get  about probably about half a kilometer. If you're going down the highway and you see like some  faraway objects, you can kind of see them like getting closer to you as you move. So that's kind  of neat. So let's talk about what you might be able to do to improve on this sort of stuff. One  thing was what I was talking about before. I'd really like to do an inertial star system. And  unfortunately I've been having some problems with the accuracy of the accelerometer in gyro. I'm  going to be working on that in the near future to try to get that accurate enough for my purposes so  I can do position tracking for basically a few seconds enough to capture the image. And so what  we would do is we basically use a gyro and accelerometer to figure out relative position and  orientation as I move the thing around. And the idea is that I don't have to measure that. I don't  have to like, you know, carefully annotate what I'm doing as I'm capturing the data. It makes it  much faster. And a cool thing you might be able to do is if you take a GPS and a magnetometer,  you probably could just georeference it on a map, have the direction you're looking and just  overlay it on, you know, a Google Earth map. And at this point you can pretty much do that with a  smartphone because that's got all of those sensors. Just add that with a sensor like this and you're  good to go. You just got to write threats off of. The other thing is something that we might actually  be doing at MIT in the next few months is a phase array radar system. So what we would do there is  we'd have a set of transmit and receive antennas. And the system here is we basically switch between  pairs of them. So you might have, you know, a couple of transmit antennas, a couple of receive  antennas. Each pair of those, if they're spaced appropriately, basically gives you a virtual  antenna at a different position. And so you can just very rapidly switch between, you know, let's  say you have like eight on each side, that's 64 different pairs of antennas or 32. Anyway, whatever.  You get, I think it's 64, yeah. I get 64 pairs of like virtual antennas that you can take and you  can very quickly generate an image. And I guess, so basically what we would get with that is, I  have a video here of something that's actually been built. This was built by MIT. This is a, what is  the video? Okay. What they did here is they built a phase array radar system designed to capture  images at 10 hertz. And what's happening here is they have a metal ball in the middle. And then what  they did is they rolled another metal ball past it. And you can basically see the thing rolling in  real time past the thing. And it's pretty neat. So you see that little dot there, it just kind of  comes past. And so this is pretty fast. There's another video online which I couldn't include due  to time. There's someone like swinging a baton. And it's interesting because like I said before,  this is an overhead view. So if someone's swinging that, it looks like a spike and then it kind of  spreads out and goes back and forth and back and forth. So, you know, that's, I can play that  again. But yeah, you can see right there, it just kind of comes by. And then there's a little bit of  interference when it comes past it due to multi-path effects of the signal. Because remember, we are  looking at electromagnetic waves here. But this is the sort of capability you could, you know,  achieve with something, you know, a little more sophisticated because the real-time aspect is  really interesting. And real-time imaging, I think, would be pretty cool to implement, especially  as like a do-it-yourself thing. So I have a few more references here. I guess you can get these  from the slides. But these are some resources. This is probably enough information to build one of  these things. Maybe not with the laser cut stuff. But it's, you know, it's not that hard. I mean,  it's a pretty simple concept. And all the parts are available commercially nowadays, which is  amazing. So I guess, you know, the main reason I gave this talk is because I really wanted to see  people build something like this, you know, actually build it. And so that's kind of like my call to  action. It's like, I would love to see someone do something really cool with this stuff and come  back next year and, you know, say, okay, I'm going to give a talk on, you know, my, you know,  improvements to the system. That would be awesome. So I think that's about all I have. So yeah, I  guess if there's any questions, you know, go ahead. Yeah. Sorry. I can't hear you. Oh, well, the  coffee cans are somewhat directional. Sorry, he asked why coffee cans is opposed to a different  type of antenna. The coffee cans are fairly directional. They are really cheap because they're  coffee cans and we had them anyway. But basically it's going to be hard to see inside this thing. So  you might just have to come back later and see. But what the way this works is there's an SMA  connector in here and there's a little wire being fed into here. So this is basically a wave  guide port. It's an adapter from that little feed antenna to this larger wave guide. And then  that just, it's basically a crappy directional antenna. But you could use another for Wi-Fi, so  if you wanted to make your signal more directional, it's the exact same principle. And if you took  some of those really big Wi-Fi antennas, you could make a highly directional system just with  that. So anyone else? Yeah, he asked which microcontroller I'm using. I'm actually using a  pick. It's one of the 16-bit picks. I tend to get a lot of shit for using their parts, but in  general what I find is that they're very inexpensive. I love that. They're very cheap parts. And  this thing was like two bucks and has off the shelf USB and stuff. So it's pretty good for my  applications. Oh, yeah, that's worth talking about. So, yes, for the power requirements work. I  believe this entire system uses about 200 milliamps at 5 volts. So like I said, it's easily  powered by the USB port. It's the only power source here. The original one was powered off of  two sets of AA batteries. So that's about all you're talking about. Yeah. Okay, so this system is  operating in the Wi-Fi... Oh, sorry, I've got to do this. He asked how much could I increase the  power. The limits at 2.4 GHz, I believe, are a watt. But that's a watt. I think it's 4 watts  radiated. So you could transmit. What's that? Okay. So you could basically... You probably had to  transmit a watt and no one's going to complain too much. The problem with this is you would have to  band limit it some more. So the way this works is it does actually extend past the Wi-Fi band a  little bit. And that's why we only use it in controlled environments. But basically, we don't  want to step on anyone else's spectrum. So I wouldn't transmit a watt in that whole range. This is  like 10 milliwatts. It's pretty low. So, yeah. Anyone else? Yeah. Well, okay. What's the signal to  noise with Wi-Fi? So I guess it's pretty dual because what you see is actually with the Wi-Fi  signals, you actually see the burst on the spectrum. I'm actually... I was shocked. I didn't see that  today. I was sure someone was going to be using Wi-Fi device in here. But basically what happens is  you get these little blips in the signal. And that chirp is like fucked. It's a pretty strong  signal. And it's hard to filter out because it's not related to your signal at all. You're just  like basically sweeping right through it and you pick up all that crap. But if they're not  transmitting, it's not really a big deal. Yeah. Is the upper frequency limit defined by how easily  you can obtain a reference signal? Is the upper frequency limit defined by how easily you can  obtain a reference signal? The frequency bands that you can operate in are... It's mostly... I mean,  there's a few bands you can operate in. You pretty much are stuck to the ISM bands if you want to do  this stuff legitimately because those are what's licensed for this unrestricted or pseudo  unrestricted use. So if you go up to 5 gigahertz, it would be a little harder to find parts. Basically  as you go up in frequency, the parts just get a little more expensive. Or as you get even higher,  they can get a lot more expensive. But the big thing you want actually in a system like this is you  want wide bandwidth because the bandwidth is what's giving you that spatial resolution and the time  resolution. Anyone else? Yeah. He asked if I was looking at software to find radio systems. I think  there would be some benefit to that if you wanted to make, you know, do some... Certainly the SAR  coherent processing stuff, that would benefit greatly from an FPGA system because it does... It  can take a few seconds to process an image like that on the computer. But in this case, like the  main goal is simplicity and low cost. So, you know, if you bring in, you know, one of those... What is  it? Edis Research Board's and like the USRP or something, that's going to add a big chunk of  change to your design. But there's definitely a lot of potential there. I would say that's  absolutely worth exploring. Anyone else? Yeah. Yes, is the Doppler effect from a fast-moving  object enough to mess up your position measurement? That kind of depends on what you're trying to do.  Okay. So, I guess if it's... If you're trying to measure something moving really fast, like on the  order of, you know, like a plane or something, you might have some impact. So, I guess when I was  talking about it before, I said that something was moving three meters per second, which is like a  person walking really quickly or maybe slow jog, is producing a 24 hertz signal. At the chirp rates  I was dealing with, you know, I think 10 meters corresponded to like 667 hertz. So, it wouldn't  affect it too much. But that all depends on your chirp rate and your bandwidth and, you know, a  bunch of other factors. So, yeah. You could make it have an impact or not. And the other thing is  there's actually a way of disambiguating those. Because I didn't talk about this, but you can  chirp up and you can chirp back down. And if you think about it, the effects are a little bit  different because the Doppler shift is always going to change the frequency in one direction. But if  you chirp the other direction, it will shift it backwards. So, all you have to do is kind of  figure out what's happening there and you can disambiguate them. Is that it? Oh, got one more.  Okay. Should I keep doing questions or? Okay. Yeah, go ahead. Yeah. On that microcontroller,  it would be pretty hard. The processing power on this thing is pretty weak. It's just, it's  useful for fastly grabbing, or quickly grabbing data. If you switch to like a DSP or like, you  know, an ice arm or an FPGA would be, you know, probably the best option in that regard. You  could definitely do that. It's not, it's not a very computationally intensive process. I mean,  this is like a Python script I was running to do the FFT.  Oh, okay. Yeah, yeah. So, to some extent, actually, for the SAR stuff, we want something a little  less directional than that. Part of it is that the COGICANs were what was available at the time.  But, no, what? That's probably true. Yes. But, yeah, I mean, it's pretty open. You basically  get different characteristics. So, if you're trying to do the SAR imaging, having a wide  beam width is actually somewhat useful because you can get, it decreases some of your spatial  fidelity, but you also get a wider image. So, if you have a very narrow beam, you're not going to  get any signal from something that's, you know, further apart. So, it's a trade-off there.  Anyone else? Okay. I guess if there's anyone else that wants to, like, see the system closer  or talk, I think I'm going to move over to the Q&A room. So, yeah, thanks for, thanks for  hearing my talk. That's great.
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Okay. Hi everyone. My name is Michael Scurrito and I'm going to talk to you about how you can build your own radar system. So this talk is a little bit off the wall, I guess. You know, traditionally it's more security focused at DEF CON, but I thought it was a pretty cool topic and I like remote sensing systems, so I wanted to present something that I've been working on with some people at MIT. So when talking about stuff like this, there's going to be some amount of math. I mean, there's not really any way to avoid that, so I do apologize in advance, but you know, we're going to talk about it and hopefully I'll explain it in a way that you can understand pretty easily. But I didn't want to, you know, kind of overwhelm anyone with it, so I'll try my best. I agree. So first of all, what is radar? Basically, it's some way of looking at the world through radio waves. You know, you're measuring something, you're sensing some sort of electromagnetic field and basically what you're doing generally is you send out a pulse and you look at the response. So radar used to be an acronym, it's become a word, it stands for radio detection and ranging and that's basically what it is. So, you know, what you might think of traditionally is something like, you know, these, I think that's a weather radar from like the 40s or something. So, you know, that's kind of the basic idea of what people think, but we can, what you're measuring is essentially position of something, velocity of something, direction of motion of something. But the thing is you can actually do a lot with this type of technology. You can look at pretty much anything. I mean, you can look at like here we've got people, you can look at terrain like land surface, you can look at, you know, foliage, weather patterns, you can look at clouds, rain, ships, aircraft, spacecraft, like pretty much anything you can think of. So, I'm not really talking about something like this, but what we can do today is more something like this. This is an image of the capital. I guess this is a Sandia radar system, but this is what synthetic aperture radar can really do with a nice system. So what we have is a 3D point cloud of the capital building taken from an aircraft. So, you know, why do it yourself? Why is this, you know, something that we could talk about now? And the reason that, you know, it's particularly interesting nowadays is because it's become extremely easy to do this and it's become cheaper than it ever was before to do this. And the big thing was the wireless revolution has given us access to a lot of hardware that used to be really expensive and pretty much only available to the military, but the need for it in the commercial communication space means you can buy a lot of this stuff just off the shelf. And the other thing is for processing, all this stuff used to be done in analog. Nowadays, you can just feed it into a computer and the computer will do pretty much everything for you. And I guess, you know, the main reason to do it yourself is because it's pretty cool. You can do some pretty interesting things with it. You know, the stuff that I'm going to demonstrate today, hopefully, is not even close to the extent of what you can do. I just want to give a simple demo of, like, you know, in this space, what can we look at? So who am I? I'm from MIT. I'm an electrical engineer, mostly, and the rest of the time I do pretty much anything else engineering or science related when I need to. Currently, I'm working on RF remote sensing systems, not radar systems, but actually weather instrumentation at MIT. And I have a pretty broad set of interests, but a lot of stuff related to RF technology, including RFID, communication stuff, imaging systems, remote sensing, wireless comm, and, you know, security, of course, is a big interest of mine. And anything that can combine those issues is awesome. So I guess what I'm going to start with is talking about how radar works in a general sense. Then I'm going to go a little more detail, like, how would you actually make some of these measurements I was talking about with the radar system? After that, you know, talk about how you could build your own radar. Hopefully, we can demo it if it works for me. I'm going to go into a little more about synthetic aperture radar, which is basically a technique for taking pictures with radar. And this is both 2D and 3D imaging. And then we'll go into maybe improving the design of the home-built radar, like, what sort of stuff I'm looking to do in the future and what stuff I'd love to see some people here talking about next year if they did it themselves. So first with an overview. Like I said before, the basic idea is, you know, we transmit a signal and we get some kind of return off of it. So, you know, this is an aviation system. So basically what this is doing is it's spinning around, sending out a pulse and measuring how long it takes to come back. But it's not necessarily that specific. You could do a lot of processing with that return signal. And the key point here is that every radar system works on this type of principle. You're transmitting a signal from somewhere or somebody is transmitting a signal from somewhere and you're looking at how that reflects off of a target. And all this is governed by this thing called the radar equation, which is this big thing with a whole bunch of terms that, you know, there's a whole bunch of stuff here. So basically what we're looking at is the function of received power versus transmitted power. And the way that that gets changed is, you know, you get transmitter gain, antenna aperture, which is like how big your dish is, cross-section, propagation factor refers to the medium that you're in. I actually don't really care about most of this stuff right now. The main point I want to make is this target distance here. So we have power over r to the fourth. That means that basically, you know, your transmit power doesn't matter that much. So the received power is going to decrease with the fourth power of the distance. So if you move by a factor of 10 away, like, you know, I guess my example here is if you receive a signal of one milliwatt at 10 meters at a kilometer, that's 10 picawatts. It's really fucking tiny. So, you know, but that sounds kind of bad because it does severely limit your range. But at the same time, the system right here that I'm going to show uses about 10 milliwatts of transmit power. That's only 10 times worse than 100 watt radar, which would be like the size of a car. So you really, you can get a lot of performance with kind of these low cost, like, simple systems. So where's radar used in general? It's pretty much used for anything. I'll go over a couple applications. Air traffic control is a really big one. They use it for in-route tracking. So this is actually a picture from a website you can go to to like track flights live. It's kind of neat. So this is Las Vegas a couple days ago. It's used for weather measurement. It's a huge set of data for trying to track precipitation. So what's happening here is this is this is a Doppler radar image. So what it's doing is it's actually measuring the velocity of the rain or the hail or whatever it's looking at. And the color is the strength of the return. So it's how much precipitation is there. But the other cool thing is they can figure out which way the storm's moving by the Doppler shift or the signal, which is why it's called Doppler radar. Another thing is, you know, police applications. They use speed guns to, you know, give you tickets and that sucks. But, you know, it's a lot of uses. On the automotive side, there's actually a lot more of this stuff. So anytime you want to kind of track things that are close by, there's radar systems there. Also, LiDAR, to some extent, which is pretty similar. But they're using it for cruise control now so your car can follow a certain distance behind the next car. Collision avoidance, your car will pie the brakes right before you hit something. Automated parking, which I think is in the Prius, uses radar to figure out where the parking spot is. And then, you know, autonomous vehicles in general are going to need a ton of this technology to figure out where they are in like the near space. It's used for surveying applications. So you can fly a plane over some terrain and get a 3D image of what the train looks like. That's pretty useful. And the military uses it for practically everything. They love radar. You know, it's hard to get some good examples, but, you know, pretty much any system that involves, you know, shooting something somewhere or like looking at something or, you know, anything that they might want to do is going to use some sort of radar system. And like I said, it's kind of hard to get good examples. So why radio frequency? You know, you can, there's tons of sensing systems that operate from, you know, basically extremely low frequency, maybe like tens of kilohertz, even lower, like tens of hertz, all the way up to visible light beyond like X-rays and everything up there. So, you know, what's special about this frequency band? And by the way, what we're talking about is something in the range of 50 megahertz to about 50 gigahertz. So, and more recently, we've been going up from there. But what's special about this range is we get pretty good propagation in the atmosphere. So we can transmit a signal that runs thousands of miles or thousands of kilometers. And it can go through the atmosphere, through space, not so much through water because it's hard to propagate through that. And that's why we have a seminar. But the signals are, you know, they can travel through clouds or smoke obscuration. To some extent, with certain systems, you can penetrate the ground. And there's something called ground penetrating radar for searching for tunnels or wiring or anything under there without actually digging it up. The signals travel really fast. Which is both a positive and a negative. So the plus side is, well, you know, it's, you're getting your signal there really fast. You can detect things really far away in a short amount of time. Like Sonar could take minutes to go any real distance. But, you know, this is, oh, this is instantaneous. 300,000 kilometers a second, I think is like six or seven trips around the world in a second. And the other advantage is that the antennas are reasonably sized. So we used to use systems that were lower frequency, hundreds of megahertz, tens of megahertz. And anyone that does amateur radio knows how freaking big those antennas are. And if you want a directional antenna, it's going to be even bigger. Because that dish is going to be 50 meters, 100 meters. That is enormous. So we can build stuff with like, you know, a can. This is at 2.4 gigahertz. This can is what, three inches in diameter. And it's coffee can. So, you know, how do we build these radio frequency systems? The big thing is that it's hard to build circuits that operate at these frequencies. If you think about your computer and how hard it is to get the CPU to run it, you know, four gigahertz or something, that is a chip that's about, you know, three quarters of an inch on the side. It's trying to switch at that frequency and get a signal three quarters of an inch or less. And that's at four gigahertz. If we want to build something that's like a transmitter at 50 gigahertz, that's going to be really hard to like do any sort of complex digital coding or modulation or anything like that. So the way that virtually every single radio works is what they do is they process the data at some low frequency. So like, if you have a, you know, a voice like FM radio or something, the transmitter is just recording audio and it's processing audio. And then when it gets ready to transmit, it just magically shifts that signal to the frequency it's transmitting at, up to, you know, 100 megahertz or something. And what this is called is heterodining. Radar pretty much works the exact same way in almost every case. So the way this works is there's a little more and more math here. So the trig identity that I'm looking at is the product of some role. Basically, if you multiply two trig functions or two sine waves at two different frequencies, what you get out is the sum of the, there's some, the frequency of their sum and the difference of the two frequencies. And you lose half the power basically in the process of doing that because the two signals are, you know, half. So what this is called is mixing. So what we're getting, you know, the sum in different, different frequencies. So as an example, if you take your 2.4 gigahertz like Wi-Fi signal and you mix that with something that's very slightly higher, this is 2.400001 gigahertz, then you get something at about 4.8 gigahertz, which you don't really care about because, well, I don't know, I don't really need it. And you get something at 1 kilohertz, which is actually a lot more interesting. So I can measure very precisely what the frequency of that second signal is if I'm very good at measuring the first one because they're really close to each other. And, you know, I can get this 1 kilohertz like resolution, for instance. That's pretty useful. So there's a device called a mixer, which basically multiplies some known signal with your unknown signal and it shifts it in frequency. And that's just magical. You can do, that's how radio is possible. So as a visual example of this, we take two functions, which I just got an octave. You know, we have sine of t, sine of 1.1 times t. So that's something that's like 10 percent faster in frequency. If you multiply those, you get something like this. This is, what you can see here is the sum of two signals. One of them is a fast moving signal and the other one is a slow moving signal. So, you know, looking at in the frequency domain, it's the same sort of thing. And this is actually a relevant picture. So if you haven't done some stuff like this before, it could be a little bit foreign to you. But basically what we're looking at with these arrows is that's indicating that there's a continuous wave tone. That's the sine wave at that frequency. And it has no energy in any other frequency. So that sine wave in time is equivalent to that spike or delta in frequency. So in this third example, what you get out is these two different frequencies. And as an example of this, you've probably heard this before. If you have a bunch of like case fans in a computer, for instance, you can get those really annoying like very time varying tones. So if you have something running like 6,000 RPM and one running at like 6,010 RPM, you have a 10 RPM signal that's being generated acoustically between those two things. So you have some faster signal and then you have this slower one. And that's going to give you that like beating tone, which is really annoying. That's exactly what's happening there. So let's talk a little bit more about what we can measure here. So like I said before, there's a couple things that we're talking about. Direction is like, if I have some target, which, where do I go to get to it? Range is the distance to the target. And velocity is kind of how fast the target is moving. So then we can combine all these things into basically imaging. So we can use various techniques to generate a 2D or a 3D picture, which is what I'm calling this range and cross range domain of one of these measurements. And when I say range and cross range, what I mean is in the radar world, if you take a picture of like this wall, for instance, or that wall, whatever, your two dimensions are kind of like up and to the side. They're both perpendicular to you. The radar kind of flips that 90 degrees. So one of your dimensions is range, which is like how far away the thing is. And the other one is like in some other axis. So it's cool because you can look from the side and then get like kind of an overhead view of what something looks like. So if we want to measure range, it seems pretty simple, right? We send out a pulse, you know, just hang it out and wait for the response. And we just time how long that takes. So here's a visual depiction here. If we have a transmit pulse at time zero, then, you know, we're going to get some returns from some targets. And we're going to say one is like, I don't know, 15 meters away. One is 30 meters. One is 65. And so that seems pretty easy. We just look for them like a scope or something. And the reason that this is hard is because the waves travel really fast. They travel at the speed of light. So we have this equation. The time it takes to get back is two times the distance because it has to go there and come back divided by the speed of light, which means that at 70 meters, we're talking about, I guess, that's 500 nanoseconds of time, which is pretty hard to measure if you want to do it easily. So if you're using a sound card, for instance, which is what the original version of this thing actually used to sample, that 44 kilohertz sample rate corresponds to a 7 kilometer distance in space and range. So, you know, that's probably not going to work for most systems. So if we're trying to measure velocity now, and I'm going to go back to range in a second, let's say we want to measure a person walking. Well, they move really slow. So it's going to be kind of hard to, like, see a real change, right? So the way this is done is with the Doppler effect. If we have something moving, like this is, I guess, the car analogy, you know, we have a car driving by on the road and you're standing there on the side of the road and you're listening to it. When it's coming towards you, you know, it sounds a little bit higher pitched. It passes you and the frequency suddenly drops and it sounds lower pitched. And that's because any, like, sound being generated by the car is basically being, like, compressed in space as it propagates because the car is moving as those waves are coming, you know, emanating from the car. So it's a higher frequency tone and it's a lower frequency tone. So if we send a radar pulse, like, what I'm calling a continuous wave tone, which is just a sine wave, at something that's moving towards you, it's going, when it reflects that, it's going to increase the frequency because it's moving faster. It's not going to change the propagation speed because everything moves at the speed of light, you know, due to relativity. But it's going to compress it in time, or in space, rather, so it's going to increase the frequency of the signal. So, you know, if we had a three meters per second signal, we're turning that 2.4 gigahertz into 2.4 plus 24 hertz. So that's going to be pretty hard to differentiate. But if we have a really good 2.4 gigahertz reference, we can just mix with that and we get out 24 hertz. And I can see that on a scope pretty easily. I can measure that. And then that way I know pretty accurately how far away the target is. And by the way, the previous example was kind of how radar first got developed. It was, that's like basically a pulse radar. This would be called continuous wave operation, which basically means you're transmitting one frequency all the time. So, going back to measuring range, if we're trying to see a difference in frequency, it's pretty easy. We can do that. And the really cool thing is if you take that into the computer and Fourier transform it, you can very easily get a plot of the frequency at, you know, versus power. And it's harder to see a difference in time just because we can't sample that fast or it's expensive to sample that fast. So, what if we took the frequency that we're transmitting that we're, you know, we have plotted here and we just ramp it? So, what that means is it's going to be a tone that looks sort of like this. It's, this is called a chirp. And what's happening is, you know, it starts out at a low frequency and it just gets faster and faster and faster and then it's done. And then it restarts or goes back down or something. So, what happens with the return signal then if you're trying to transmit it at something that's far away is, you know, you get, like, let's say the first line is a transmitted signal and the second line is the received signal. So, you have, if you're looking at what you're transmitting at a given time compared to what you just received, it's going to be shifted by however much time it took between, you know, when you sent it and when you just got it back. And so, that's some small amount of time. But if you're ramping the frequency, it actually corresponds to a difference in frequency. And then you can actually do the exact same thing. If you mix those two signals together using a mixer, you will get out basically the difference in frequency between the two signals. And what that means, you know, practically is, let's say we have a 10 meter target or, you know, something that's 10 meters away. If we ramp over 200 megahertz in 20 milliseconds, which is reasonable, you know, it's something that we can achieve pretty easily, that, you know, point, whatever the hell that is, I don't know how long that is. But I think it's 66 nanoseconds or something. That signal turns into 667 hertz, which is in the middle of the audio range. I could sample that with a sound card and tell you how far away you are. So, this is known as FMCW radar, Frequency Modulated Continuous Wave. And that's how I think most of the systems work today. So then, you know, let's say we want to go a little bit further and then we want to take a picture of something. So, there's a few ways of doing that. But basically, at a high level, what we're doing is we're basically just taking these measurements and just repeating them again and again and again in some different place or different orientation or whatever. So, there's a few ways of doing that. One is just scanning. So, if you've ever seen a big dish just spinning around repeatedly, you'll probably seen them at airports before. All that's doing is it's a very directional beam and it's just pointing it out and measuring the responses back to try to find all the planes. And so, it just scans and it, you know, just traces out a path. And it's exactly what you see on those old radarscopes where you have a line going around your little circular screen. So, you know, we've gotten a little bit more sophisticated in that sense then. So, there's something called synthetic aperture radar which basically means you can get better resolution if you have a bigger dish. But the problem is then you have a bigger dish. And the bigger dishes are more directional, so that's the advantage. So, with synthetic aperture radar, what you're doing is you're actually taking coherent measurements of the signal at different places and you're trying to simulate having a larger dish. And, you know, the reason you would do that is so that you can get a finer resolution of space. So, if you just point it in one direction, like, I think the beam was on these things were like 40 degrees or something. So, you couldn't see shit out there. But the idea is that you make it highly directional by simulating measurements from multiple places and then you can kind of combine all those measurements together and get a, you know, range cross range plot. And I can't do that live right now, but I will show you some pictures of that. And then, you know, another system is actually called Inverse SAR where you actually, you keep the radar fixed, but you move the target. And this is if you want to get like kind of radar cross-section measurements of an aircraft or something. I'm not sure why you'd want to do that. But, you know, yeah. And then more recently, something that they've been doing is called, it's basically multi-antena beamforming. And beamforming is where you take a whole bunch of antennas and you, instead of having like a directional beam to begin with, you basically steer the beam with the antennas. And the way that works is you're basically adjusting the phase of each signal so that you have some flat front in some direction. And you can control that direction and scan really fast. And the advantage there is you have no moving parts and you can scan really, really quickly. And we use, you know, we use that for a bunch of surveillance applications. Like it's just, it's useful if you want to find things really fast. And it's much more flexible than something that just physically scans. So, you know, let's go on to, you know, how you might build a system like this. So, I, the home-built radar that I have here, which I guess if you want to get a good look at it, I guess come to the Q&A room and we can show it off. The original design was by this guy named Greg Charvet. He's an employee at MIT and, you know, I've worked with him a good bit and he's a pretty cool guy. So, he's, he really loves radar. And so he designed this system to be built as an MIT class, as basically a, I think it's a two-week long class where you just learn how to build these things. And it's, it's pretty simple. The cost is a few hundred dollars. It operates in the Wi-Fi band, 2.4 gigahertz. And it's, it's pretty simple to use. The downside, at least with the one that I built, is that it's actually really hard to get through airport security. They give you a lot of shit if you try to take something like that on the plane. What I, what I was told when I went through the check-in was that, well, I, I, I showed, I flagged the guy down and I showed him this thing and he's like, what the hell's that? And I tell him it's a radar and he's like, what's that? So, so, you know, I was like, okay, you can look in here or something. And then, you know, his comment was perfect. He's just, he just says, it looks like a bomb. And I was like, well, I'm glad I didn't say that. But anyway, eventually they did let me through and I was able to get here. Hopefully I'm not on a watch list now. So, let's try to, let's try to describe how the system works. So, this is a, this is a block diagram for RF stuff. And I guess it's, that's not too hard to read up here. So, this is how RF engineers kind of like deal with the world of circuit. So, we know, this isn't really a circuit. It's a set of components. So, you know, I'll try to go through it and explain what's happening here. So, the first thing is, the thing that says modular, that little like spike thing is, that's the ramp generator. It's generating just a ramp and voltage, which gets fed to this thing with the curvy line called a voltage controlled oscillator. And it does exactly what you think. The frequency of oscillation is related to the input voltage. So, you send it a ramp and it gets faster and faster. And that generates the chirp I was talking about earlier. There's an attenuator, a power amplifier, which just makes the signal, you know, louder, more powerful. That signal gets split. And one of the, you know, one of the copies of the signal gets transmitted out by, you know, one of these, one of these dishes here, coffee cans, sorry. The other one, the other part of the signal goes to that mixer. And that's what I said before, was the local oscillator for that mixer. So, then what happens is the signal gets sent out by one antenna. It gets reflected off of whatever. And then it comes back and the other antenna gets amplified again because it's going to be really, really weak. Now, remember that one over R to the fourth thing I was talking about. And then it gets mixed with that known signal. So, then it basically, what we did is we took a signal and we shifted it all the way down to pretty low frequency near DC where we could record it. With the original system for this, used the sound card. I've actually changed that a little bit since then. But that's what's cool about this, is you can literally build something like this and record your radar data with your sound card. And just process it on the computer with, you know, you record with audacity and then process it in MATLAB. That was how the original system worked. And then there's this thing down here called a video amplifier. And what that does is it basically just takes that really small signal that's still pretty small and amplifies it a bunch of times at low frequency so we can feed it out to the computer. And there's two outputs to this. One of these is the sync pulse which basically tells us when the chirp starts and then the other one is the actual data signal back out. And then I guess the components are here. You can get those slides later. But these are all off the shelf parts from this company called Mini Circuits which builds these things. They basically, they take a little chip and they put it in the package and do all the testing to make it actually work. And then you just like screw on little SMA connectors to it. It's pretty cool because you just, it's like doing plumbing but you're building an RF circuit. So here's a picture of the thing that's sitting right there. I guess, I think I have call outs on the next page. So basically these are all the parts I just talked about. It's a little bit different than that diagram because that green board is not in the original design. That's actually basically a USB data acquisition board that I developed for this. And I'm working on getting that to be releasable but right now it's not quite ready for public use yet. But eventually I'd like to just kind of publish the designs online. So you can see all the components I was talking about before. We have, you know, the VCL first which gets a signal from that green board which is actually generating our ramp now. So it's computer controlled. So the VCL goes to the attenuator, goes to one of those amplifiers and then you see the splitter out there. One of those signals goes to the transmit can antenna which you can see at the bottom. And then, you know, the other signal goes to the mixer. The received signal goes to one of the other amplifiers into the mixer and then everything goes out to the video amplifier and then back into the board. So that's basically, you know, that's pretty much all the components we just talked about. I guess just for completeness I'm not going to explain these schematics but this is the original circuit. This is something you could build yourself really easily to do data capture. So one of these things is the video amplifier, that thing at the, you know, the box thing at the top. And the other one is the ramp generator which is just a chip that generates ramps. And it generates two output signals which you plug into your sound card and record your radar data. Yeah? Sorry? Yeah. Oh, so the reason that's there is because when I was trying to make this in USB powered and so I just wired it onto the power for this other stuff. Everything on here runs off of 5 volts. So I plug the USB in and then the computer doesn't like that. It just turns off the port. So the problem was the interest current was too high and I needed something to like slow that down. So I was like, okay, I'll put an inductor in there. And the only thing I could find was this big like choke transformer thing. So I just shoved that in there and that worked. So that's all that's for. Okay, so let's say we want to do a little bit more. We want to get a little more sophisticated in the sound card because there are some disadvantages there. It's hard to collect every chirp. It's hard to stay synchronized and it's not as fast as we might like for sample rate. So I developed this board that's basically a microcontroller with an A to D, D to A converter. The way that we generate the ramp is we take a digital signal in the D to A converter and then feed it through an integrator. And if you remember your signals and systems, that continuous line turns into a ramp and we can control the speed of that ramp. And the reason that we're not just directly generating the ramp is because if you ever looked at how a DAC outputs a signal, every time you switch it, it like jumps to the next level a little bit. It doesn't like kind of smooth it out. So we could filter the hell out of it and it probably wouldn't work or we could just do something like this where we just generate a flat signal and then in analog we make the ramp. And that was the easiest option and it works pretty well. And then we just send that out to the VCO. And then on the receive side, you know, we have a video amp that was actually not on the green board, sorry, on the other board there. And then there's an A to D converter which is way faster than the other one. I think you could actually run it 500,000 samples per second, which is a lot faster than your sound card at 44, 96 or something like that if you have a nicer one. And the other advantages are, you know, internal triggering which basically means I start the ramp and I know where the ramp is and then I start to capture at a certain point. I capture data really fast and then it's done and I send it back to the computer. So it's completely kind of self-contained. I don't have to deal with like processing it later to do the triggering. And that makes a lot of the real time stuff a lot easier. So this is a picture of the board. I guess there's not really too much to say here. It's just, you know, yay circuits. And then there's a call outs on that. So actually the two other things on there that I didn't mention was the gyro and accelerometer. And I haven't really gotten to using these yet, but this is part of my future plan is, well, if we can just track the position of the thing, we can do a lot of this kind of coherent imaging stuff without any effort. And I'll talk about that a little more later. So I'd like to try a demo now. I really hope this works, but, you know, I'm not, I know how demos work at DEF CON tonight. I'm not, you know, we'll see what happens. But basically what we're going to do is we're going to try to do a range finding demo. So I'm going to take this thing and set it up to basically generate a chart, record the response and display it on the screen. And what's going to happen is there'll be a couple of plots there and I'll describe those when they come up. But basically what you should be able to see is the distance to a wall or something is going to come up as a stronger signal at some range. And we'll plot it with respect to range. And then all that processing is done with an FFT. So let's see if I can get out of this. Okay. Oh, wow. That worked surprisingly well. So if I plug this under the computer. So we have to hope that VM or properly captures the device because sometimes it doesn't like to. Let's just confirm that. It looks like it's connected. So a little Python program. I actually found this program online. It was just like something to generate an audio spectrum. And I was like, well, it's Python. It's going to be really easy to make it do whatever the hell I want. So I adapted it to my little USB serial interface. And actually I should probably, I think I'm forgetting something. I got to set the mode on this. Sorry. Whatever. Let's see if this works. So it doesn't give any error messages. We should be getting something scrolling across the screen in a second. Oh, okay. So there's a couple different things here. So in the middle plot, there's actually a lot of noise here. And I can explain why that probably isn't a little bit. So that plot in the middle is basically the time plot of the signal that we're sending out. Or this is the response. So this is literally at low frequency. It's basically an audio tone is what it would sound like. And that's related to the signal. It's not very directly related. So what we do is we Fourier transform that, which you can see on the left and the right. So the one on the right is kind of a scrolling view of that. And it's kind of hard to see the scale on here. But on that spectrogram view, those numbers are supposed to be the distance in meters to whatever you're looking at. So I guess you've seen a fish finder before. It's basically the same interface. So what I can do is I point it at the wall. I'm pretty sure that that strong response at about 30 meters is probably about the distance to that, which sounds about right. I point it up at the ceiling. It's going to drop down. And we see a very strong red line at about eight. You know, it's about the correct distance. And we can just kind of scan it around. You know, so, sorry? Yeah. So we get something at about four, which is, right. So, you know, it's basically, you can also see the power thing here. So when this is being displayed, this is a log scale. So it's not going to decline as fast as you would expect. But as they get further out, obviously the signal gets way, way weaker. And the other thing, which I haven't actually seen yet, which I'm a little surprised by, is so this thing operates in the Wi-Fi band. There's a lot of noise. I'm not exactly sure why that's happening. That was happening before. But what you do see occasionally is these pulses kind of towards the top end of that. And that's actually Wi-Fi signal bursts from the thing transmitting. It's a, you know, I think it's a 20 megahertz wide signal. And what you see that for is like a little pulse in the middle of the time window. And unfortunately, I guess no one's using Wi-Fi devices in here because I'm not picking anything up. So I guess everyone's being smart now and they're not using Wi-Fi at DEF CON. But yeah, I mean, this is basically, you know, that's all there is to it to doing something, you know, pretty simple. So literally all I did here is I'm recording the analog signal. I'm 4A transforming it and displaying it on the screen. And that's all there is to it. So let's go, let's go there. So let's head back to the talk. I'm glad that worked. So let's talk a little bit about, you know, trying to image with one of these things. So synthetic aperture radar is basically the idea of instead of having, you know, a really big antenna or a lot of little antennas, let's just take this thing and like move it, like slide it down a table or something and just keep taking images. And there's two basically techniques of doing that. One is basically kind of scanning around the object that you want to look at and it's called spotlight SAR as you might expect. The other option is basically trying to scan your radar across a scene and getting, you know, basically getting these repeating pulses to the side. And that's actually, it's a little easier to process. So that's how this was originally working. And I'll give you an example of that in a second. Basically what you're doing is you take these pulses and you can get a lot of information about the phase of that signal. So that analog signal that I showed you in the time domain is actually pretty important because all the phase of those frequencies affects like subtly the difference between, you know, your transmitter and various elements of the target. So you can kind of coherently combine those and get a 2D image. So this is an example that Dr. Charvet gave me of what he built with something that's very similar to this using the same sort of specifications. So we have a 2D image from Google Earth and he went out to this field and he did this. I think, I mean, you know, you move the, basically you move the radar about eight feet and you get an overlay image like this. So I'm going to go back and forth a couple of times. But what's cool is you're basically looking at the foliage from the tree. So you get all those red areas are basically where there's something that return. And the other thing is you can see that telephone pole or whatever the hell that is right there is also giving a pretty strong return. And the range on this is like a couple of hundred feet. So it's actually pretty good. I was testing this in my car at one point and I was actually able to get about probably about half a kilometer. If you're going down the highway and you see like some faraway objects, you can kind of see them like getting closer to you as you move. So that's kind of neat. So let's talk about what you might be able to do to improve on this sort of stuff. One thing was what I was talking about before. I'd really like to do an inertial star system. And unfortunately I've been having some problems with the accuracy of the accelerometer in gyro. I'm going to be working on that in the near future to try to get that accurate enough for my purposes so I can do position tracking for basically a few seconds enough to capture the image. And so what we would do is we basically use a gyro and accelerometer to figure out relative position and orientation as I move the thing around. And the idea is that I don't have to measure that. I don't have to like, you know, carefully annotate what I'm doing as I'm capturing the data. It makes it much faster. And a cool thing you might be able to do is if you take a GPS and a magnetometer, you probably could just georeference it on a map, have the direction you're looking and just overlay it on, you know, a Google Earth map. And at this point you can pretty much do that with a smartphone because that's got all of those sensors. Just add that with a sensor like this and you're good to go. You just got to write threats off of. The other thing is something that we might actually be doing at MIT in the next few months is a phase array radar system. So what we would do there is we'd have a set of transmit and receive antennas. And the system here is we basically switch between pairs of them. So you might have, you know, a couple of transmit antennas, a couple of receive antennas. Each pair of those, if they're spaced appropriately, basically gives you a virtual antenna at a different position. And so you can just very rapidly switch between, you know, let's say you have like eight on each side, that's 64 different pairs of antennas or 32. Anyway, whatever. You get, I think it's 64, yeah. I get 64 pairs of like virtual antennas that you can take and you can very quickly generate an image. And I guess, so basically what we would get with that is, I have a video here of something that's actually been built. This was built by MIT. This is a, what is the video? Okay. What they did here is they built a phase array radar system designed to capture images at 10 hertz. And what's happening here is they have a metal ball in the middle. And then what they did is they rolled another metal ball past it. And you can basically see the thing rolling in real time past the thing. And it's pretty neat. So you see that little dot there, it just kind of comes past. And so this is pretty fast. There's another video online which I couldn't include due to time. There's someone like swinging a baton. And it's interesting because like I said before, this is an overhead view. So if someone's swinging that, it looks like a spike and then it kind of spreads out and goes back and forth and back and forth. So, you know, that's, I can play that again. But yeah, you can see right there, it just kind of comes by. And then there's a little bit of interference when it comes past it due to multi-path effects of the signal. Because remember, we are looking at electromagnetic waves here. But this is the sort of capability you could, you know, achieve with something, you know, a little more sophisticated because the real-time aspect is really interesting. And real-time imaging, I think, would be pretty cool to implement, especially as like a do-it-yourself thing. So I have a few more references here. I guess you can get these from the slides. But these are some resources. This is probably enough information to build one of these things. Maybe not with the laser cut stuff. But it's, you know, it's not that hard. I mean, it's a pretty simple concept. And all the parts are available commercially nowadays, which is amazing. So I guess, you know, the main reason I gave this talk is because I really wanted to see people build something like this, you know, actually build it. And so that's kind of like my call to action. It's like, I would love to see someone do something really cool with this stuff and come back next year and, you know, say, okay, I'm going to give a talk on, you know, my, you know, improvements to the system. That would be awesome. So I think that's about all I have. So yeah, I guess if there's any questions, you know, go ahead. Yeah. Sorry. I can't hear you. Oh, well, the coffee cans are somewhat directional. Sorry, he asked why coffee cans is opposed to a different type of antenna. The coffee cans are fairly directional. They are really cheap because they're coffee cans and we had them anyway. But basically it's going to be hard to see inside this thing. So you might just have to come back later and see. But what the way this works is there's an SMA connector in here and there's a little wire being fed into here. So this is basically a wave guide port. It's an adapter from that little feed antenna to this larger wave guide. And then that just, it's basically a crappy directional antenna. But you could use another for Wi-Fi, so if you wanted to make your signal more directional, it's the exact same principle. And if you took some of those really big Wi-Fi antennas, you could make a highly directional system just with that. So anyone else? Yeah, he asked which microcontroller I'm using. I'm actually using a pick. It's one of the 16-bit picks. I tend to get a lot of shit for using their parts, but in general what I find is that they're very inexpensive. I love that. They're very cheap parts. And this thing was like two bucks and has off the shelf USB and stuff. So it's pretty good for my applications. Oh, yeah, that's worth talking about. So, yes, for the power requirements work. I believe this entire system uses about 200 milliamps at 5 volts. So like I said, it's easily powered by the USB port. It's the only power source here. The original one was powered off of two sets of AA batteries. So that's about all you're talking about. Yeah. Okay, so this system is operating in the Wi-Fi... Oh, sorry, I've got to do this. He asked how much could I increase the power. The limits at 2.4 GHz, I believe, are a watt. But that's a watt. I think it's 4 watts radiated. So you could transmit. What's that? Okay. So you could basically... You probably had to transmit a watt and no one's going to complain too much. The problem with this is you would have to band limit it some more. So the way this works is it does actually extend past the Wi-Fi band a little bit. And that's why we only use it in controlled environments. But basically, we don't want to step on anyone else's spectrum. So I wouldn't transmit a watt in that whole range. This is like 10 milliwatts. It's pretty low. So, yeah. Anyone else? Yeah. Well, okay. What's the signal to noise with Wi-Fi? So I guess it's pretty dual because what you see is actually with the Wi-Fi signals, you actually see the burst on the spectrum. I'm actually... I was shocked. I didn't see that today. I was sure someone was going to be using Wi-Fi device in here. But basically what happens is you get these little blips in the signal. And that chirp is like fucked. It's a pretty strong signal. And it's hard to filter out because it's not related to your signal at all. You're just like basically sweeping right through it and you pick up all that crap. But if they're not transmitting, it's not really a big deal. Yeah. Is the upper frequency limit defined by how easily you can obtain a reference signal? Is the upper frequency limit defined by how easily you can obtain a reference signal? The frequency bands that you can operate in are... It's mostly... I mean, there's a few bands you can operate in. You pretty much are stuck to the ISM bands if you want to do this stuff legitimately because those are what's licensed for this unrestricted or pseudo unrestricted use. So if you go up to 5 gigahertz, it would be a little harder to find parts. Basically as you go up in frequency, the parts just get a little more expensive. Or as you get even higher, they can get a lot more expensive. But the big thing you want actually in a system like this is you want wide bandwidth because the bandwidth is what's giving you that spatial resolution and the time resolution. Anyone else? Yeah. He asked if I was looking at software to find radio systems. I think there would be some benefit to that if you wanted to make, you know, do some... Certainly the SAR coherent processing stuff, that would benefit greatly from an FPGA system because it does... It can take a few seconds to process an image like that on the computer. But in this case, like the main goal is simplicity and low cost. So, you know, if you bring in, you know, one of those... What is it? Edis Research Board's and like the USRP or something, that's going to add a big chunk of change to your design. But there's definitely a lot of potential there. I would say that's absolutely worth exploring. Anyone else? Yeah. Yes, is the Doppler effect from a fast-moving object enough to mess up your position measurement? That kind of depends on what you're trying to do. Okay. So, I guess if it's... If you're trying to measure something moving really fast, like on the order of, you know, like a plane or something, you might have some impact. So, I guess when I was talking about it before, I said that something was moving three meters per second, which is like a person walking really quickly or maybe slow jog, is producing a 24 hertz signal. At the chirp rates I was dealing with, you know, I think 10 meters corresponded to like 667 hertz. So, it wouldn't affect it too much. But that all depends on your chirp rate and your bandwidth and, you know, a bunch of other factors. So, yeah. You could make it have an impact or not. And the other thing is there's actually a way of disambiguating those. Because I didn't talk about this, but you can chirp up and you can chirp back down. And if you think about it, the effects are a little bit different because the Doppler shift is always going to change the frequency in one direction. But if you chirp the other direction, it will shift it backwards. So, all you have to do is kind of figure out what's happening there and you can disambiguate them. Is that it? Oh, got one more. Okay. Should I keep doing questions or? Okay. Yeah, go ahead. Yeah. On that microcontroller, it would be pretty hard. The processing power on this thing is pretty weak. It's just, it's useful for fastly grabbing, or quickly grabbing data. If you switch to like a DSP or like, you know, an ice arm or an FPGA would be, you know, probably the best option in that regard. You could definitely do that. It's not, it's not a very computationally intensive process. I mean, this is like a Python script I was running to do the FFT. Oh, okay. Yeah, yeah. So, to some extent, actually, for the SAR stuff, we want something a little less directional than that. Part of it is that the COGICANs were what was available at the time. But, no, what? That's probably true. Yes. But, yeah, I mean, it's pretty open. You basically get different characteristics. So, if you're trying to do the SAR imaging, having a wide beam width is actually somewhat useful because you can get, it decreases some of your spatial fidelity, but you also get a wider image. So, if you have a very narrow beam, you're not going to get any signal from something that's, you know, further apart. So, it's a trade-off there. Anyone else? Okay. I guess if there's anyone else that wants to, like, see the system closer or talk, I think I'm going to move over to the Q&A room. So, yeah, thanks for, thanks for hearing my talk. That's great.
build your own radar system. So this talk is a we're going to talk about it and hopefully I'll something, velocity of something, direction of more something like this. This is an image of the but this is what synthetic aperture radar can hardware that used to be really expensive and am I? I'm from MIT. I'm an electrical engineer, sensing systems, not radar systems, but actually is talking about how radar works in a general the design of the home-built radar, like, what is actually a picture from a website you can go And the military uses it for practically to get some good examples, but, you know, pretty examples. So why radio frequency? You know, you digging it up. The signals travel really fast. imaging. So we can use various techniques to generate a 2D or a 3D picture, which is what I'm we want to measure range, it seems pretty simple, how you might build a system like this. So, I, And so he designed this system to be built as an So, you know, I'll try to go through it and signals, you actually see the burst on the