Real-time spectrum analyzers such as the RSA6100 and RSA3400 families available from Tektronix, Inc. of Beaverton, Oreg. trigger on, capture, and analyze RF signals in real-time. These instruments seamlessly capture RF signals so that, unlike conventional swept spectrum analyzers and vector signal analyzers, no data is missed within a specified bandwidth.
Referring now to FIG. 1, a real-time spectrum analyzer 100 receives a radio frequency (RF) input signal and optionally down-converts it using a mixer 105, local oscillator (LO) 110, and filter 115 to produce an intermediate frequency (IF) signal. An analog-to-digital converter (ADC) 120 digitizes the IF signal to produce a continuous stream of digital samples. The digital samples are input to a circular buffer 125 and also input to a trigger detector 130 that processes the digital samples in real-time and compares the processed samples to a user-specified trigger threshold. When the processed digital samples violate the trigger threshold, the trigger detector 130 generates a trigger signal that causes an acquisition memory 135 to store the digital samples held in the circular buffer 125. “Violate” means either “exceeds” or “is less than,” depending on a user-specified parameter. The stored digital samples are then analyzed by a post-analysis processor 140, and the results may be displayed on a display device 145 or stored in a storage device (not shown).
Tektronix real-time spectrum analyzers use a technology referred to as “Digital Phosphor” or alternatively as “DPX®.” A DPX-enabled real-time spectrum analyzer uses a continuous-time processor 150 to process the continuous stream of digital samples from the ADC 120 in real-time and display the results on the display device 145. Referring now to FIG. 2, the continuous-time processor 150 uses a frequency transform 205 such as a fast Fourier transform (FFT), a chirp-Z transform, or the like to transform the continuous stream of digital samples into thousands of spectra 210 every second. The spectra 210 are then combined to form a data structure referred to as a “bitmap database” 220. In one embodiment, each spectrum 210 is rasterized to produce a “rasterized spectrum” 215. A rasterized spectrum comprises an array of cells arranged in of a series of rows and columns, with each row representing a particular amplitude value and each column representing a particular frequency value. The value of each cell is either a “1,” also referred to as a “hit,” which indicates that the input signal was present at that particular location in the amplitude versus frequency space during the measurement period, or a “0” (depicted as a blank cell in the Drawings), which indicates that it was not. The values of the corresponding cells of the rasterized spectra 215 are summed together to form the bitmap database 220, and then the value of each cell of the bitmap database 220 is divided by the total number of rasterized spectra 215 so that it indicates the total number of hits during the measurement period divided by the total number of rasterized spectra 215, or equivalently, the percentage of time during the measurement period that the input signal occupied that particular location in the amplitude versus frequency space, also referred to as the “DPX Density®.” The rasterized spectra 215 and the bitmap database 220 are depicted in the Drawings as having 10 rows and 11 columns for simplicity, however it will be appreciated that in an actual embodiment, the rasterized spectra 215 and the bitmap database 220 may have hundreds of columns and rows. The bitmap database 220 is essentially a three-dimensional histogram, with the x-axis being frequency, the y-axis being amplitude, and the z-axis being density. The bitmap database 220 may be displayed as an image referred to as a “bitmap” on the display device 145, with the density of each cell being represented by a color-graded pixel. Alternatively, the bitmap database 220 may be stored in a storage device (not shown). DPX acquisition and display technology reveals signal details such as short-duration or infrequent events that are completely missed by conventional spectrum analyzers and vector signal analyzers. For more information on DPX, see Tektronix document number 37W-19638 titled “DPX® Acquisition Technology for Spectrum Analyzers Fundamentals” dated Aug. 20, 2009, available at http://www.tek.com/.
DPX-enabled real-time spectrum analyzers have a measurement referred to as a “density measurement,” or alternatively as an “occupancy measurement.” An occupancy measurement indicates the percentage of time during a measurement period that an input signal occupied a particular location in the amplitude versus frequency space. A user may measure the occupancy of a single pixel of a bitmap, or alternatively the user may measure the occupancy within a specified rectangular area in of a bitmap that encompasses multiple pixels. The density of a pixel equals the number of hits within that pixel divided by the number of spectra used to generate it:
      Density of a pixel    =            Number      ⁢                          ⁢      of      ⁢                          ⁢      hits              Number      ⁢                          ⁢      of      ⁢                          ⁢      Spectra      
For example, if a particular pixel contains one hit after 100 spectra are processed, then the density of that pixel equals 1/100=1%.
The density within a rectangular area equals the sum of the densities of all of the pixels within the area divided by the number of columns bound by the area:
      Density of an area    =            Sum of densities of all pixels within the area              Number of columns bound by the area      
For example, if an area includes 3 rows and 3 columns for a total of 9 pixels, and the density of each pixel is 1%, then the density of the area equals (9×1%)/3=3%. FIG. 3 depicts a bitmap 300 having such an occupancy measurement. In order to provide a more realistic depiction of an actual bitmap, the bitmap 300 is depicted in the Drawings as having hundreds of rows and columns, the gridlines of which are not shown, and the color-grading of the bitmap 300 is depicted as grey-scale, with darker shades of grey indicating that the signal was present more often. The occupancy measurement indicates that signal energy was detected within a rectangle 305 62.614% of the time that data was being collected. For more information on occupancy measurements, see co-pending U.S. Patent Application No. 61/160,216 titled “Occupancy Measurement and Triggering in Frequency Domain Bitmaps” filed on Mar. 13, 2009.
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USPTO Backgrounds