dsmac missile
34609278
Attacking the Empty: People's Republic of China Foreign Missile Technology Acquisition and Implications on Future Technology Bans
Abstract The People's Republic of China (PRC) has improved its surface to surface missile capabilities over the last decade by acquiring foreign missile technology. Despite bans on the importation of missile related items, the People's Liberation Army (PLA) has integrated foreign technology into existing missile systems. The PLA has gained a military advantage over Taiwan and the United States due to a lack of missile defense systems to counter missile attacks. In the coming decade, the application of precision will further enhance missile capabilities. By understanding the impact of technology integration, the central question is whether a future ban on precision technology will affect the PLA s missile capabilities. By analyzing the PLA s advanced missile programs, an assessment is made on what these programs will be used for and what precision related items these programs require. Second, an analysis is made on what precision subsystems these programs lack and will likely be sought. Third, an assessment is made regarding the PRC s missile capabilities against current and future missile defenses developed by the United States and Taiwan. In conclusion, a missile gap exists that favors the PRC; however, precision technology is required to maintain this advantage and a future ban on certain technology would close this gap.
Charles T Duray
82456167
Janeway's immunobiology
Part I An Introduction to Immunobiology and Innate Immunity 1. Basic Concepts in Immunology 2. Innate Immunity Part II The Recognition of Antigen 3. Antigen Recognition by B cell and T cell Receptors 4. The Generation of Lymphocyte Antigen Receptors 5. Antigen Presentation to T Lymphocytes Part III The Development of Mature Lymphocyte Receptor Repertoires 6. Signaling Through Immune System Receptors 7. The Development and Survival of Lymphocytes Part IV The Adaptive Immune Response 8. T Cell Mediated Immunity 9. The Humoral Immune Response 10. Dynamics of Adaptive Immunity 11. The Mucosal Immune System Part V The Immune System in Health and Disease 12. Failures of Host Defense Mechanism 13. Allergy and Hypersensitivity 14. Autoimmunity and Transplantation 15. Manipulation of the Immune Response Part VI The Origins of Immune Responses 16. Evolution of the Immune System Appendix I Immunologists' Toolbox Appendix II CD Antigens Appendix III Cytokines and their Receptors Appendix IV Chemokines and their Receptors Appendix V Immunological Constants
Kenneth P Murphy Casey T Weaver Allan Mcl Mowat Leslie J Berg David D Chaplin Charles A Jr Janeway Paul Travers Mark J Walport
15252590
Development of NASA TLX (Task Load Index) Results of Empirical and Theoretical Research
Abstract The results of a multi year research program to identify the factors associated with variations in subjective workload within and between different types of tasks are reviewed. Subjective evaluations of 10 workload related factors were obtained from 16 different experiments. The experimental tasks included simple cognitive and manual control tasks, complex laboratory and supervisory control tasks, and aircraft simulation. Task behavior and subject related correlates of subjective workload experiences varied as a function of difficulty manipulations within experiments, different sources of workload between experiments, and individual differences in workload definition. A multi dimensional rating scale is proposed in which information about the magnitude and sources of six workload related factors are combined to derive a sensitive and reliable estimate of workload.
S G Hart Lowell E Staveland
141909282
The Subjective Workload Assessment Technique: A Scaling Procedure for Measuring Mental Workload
Mental workload is proposed to be a multidimensional construct that can be largely explained by three component factors: Time Load, Mental Effort Load, and Psychological Stress Load. In this paper, we describe a subjective scaling approach, the Subjective Workload Assessment Technique (SWAT) that captures this multidimensional nature of mental workload. We describe the SWAT procedure as a two phased method that includes (a) a scale development phase based on conjoint measurement and nonmetric scaling, and (b) an event scoring phase. The development of SWAT and its measurement foundations are discussed. Recent research illustrating SWAT's widespread utility and its sensitivity as a measure of perceived mental workload is summarized.
Gary B Reid Thomas E Nygren
53132108
TERRAIN REFERENCED UAV NAVIGATION WITH LIDAR A COMPARISON OF SEQUENTAIL PROCESSING AND BATCH PROCESSING ALGORITHMS
This paper discusses terrain referenced navigation (TRN) system using light detection and ranging (LiDAR) and pressure altimeter in order to compensate for an Inertial Navigation system (INS) errors. The paper addresses sequential processing such as Sandia Inertial Terrain Aided Navigation (SITAN) and batch processing algorithms such as Digital Scene Matching Area Correlator (DSMAC) and carries out simulations with scenarios in order to compare the performance of these two processing algorithms and verify which one is more useful in each specific environment.
Yeonha Hwang Min-Jea Tahk
113471789
Existing conventions and unmanned ships need for changes?
iv TABLE OF CONTENTS v LIST OF FIGURES viii LIST OF ABBREVIATIONS ix
Tomotsugu Noma
127428295
A GPS inspired Terrain Referenced Navigation algorithm
Terrain Referenced Navigation (TRN) refers to a form of localization in which measurements of distances to the terrain surface are matched with a digital elevation map allowing a vehicle to estimate its own position within the map. The main goal of this dissertation is to improve TRN performance through better signal processing. More specifically, the project aims to explore opportunities in the field of TRN by using digital signal processing techniques that were originally developed for the acquisition and tracking of GPS signals. A typical TRN system uses speed, heading and time to establish the relative horizontal position between subsequent elevation measurements. Thus, any error in speed, heading or time will cause an error in the resulting relative position. If the speed or heading error contains a bias, this will cause a gradual reduction in the correlation. To prevent that a reduction in correlation causes the estimated position to drift away, the idea behind the research described in this thesis is the use of arrays of terrain elevation measurements with intentional (positive and negative) offsets in speed and heading in a tracking loop configuration. It is well known that such a concept works well for optimized signals such as the ones used in GPS. To further explore the viability of this idea for a signal defined by a series of terrain elevation measurements, an analysis of similarities and differences with the GPS signal is performed. In accordance to the GPS receiver approach, a novel correlation algorithm for TRN is proposed and implemented. The basic rationale for the algorithm is to use terrain correlation to "acquire and track" the speed and heading of the host vehicle, while the position advances are calculated using these estimates together with the previously determined position. The novelty of the approach consists in the implementation of a tracking scheme based on the DLL concept. To answer feasibility related questions, the algorithm is first evaluated in a purely theoretical framework. Based on this analysis it is concluded that the concept seems feasible and promising, but additional considerations in the design are required to compensate for the differences between the GPS and TRN signals. Enhancements are brought to the initial design resulting in the development of an adaptive tracking scheme, in which the tracking loops are configured based on an analysis of the terrain signal. Next, an in depth sensitivity analysis is carried out to understand how sensor measurement errors (in speed, heading and terrain height) impact the algorithm performance. The analysis is performed using exclusively simulated data. It is shown that sensitivity to speed and heading errors is dependent on terrain features and it is possible to assess the degree of sensitivity by analysing the terrain signal. By combining this information with the expected error characteristic of the navigation sensors, the performance of the algorithm can be predicted. The sensitivity to terrain measurement errors depends on the ratio between the terrain signal strength and the measurement errors. It is shown that this ratio can be predicted up to a certain extent and a method to improve the ratio is proposed and discussed. The developed capabilities are validated with recorded sensor data from flight tests. Two different types of recorded sensor data are used: radar and lidar based datasets.
Dhadesugoor R Vaman
24236064
Aircraft navigation by means of image registration
Most aircraft, whether manned or unmanned, depend on the Global Positioning System (GPS) for navigation. However, GPS signals are susceptible to jamming and spoofing. A researcher recently demonstrated the use of spoofing to take control of a ship in the Mediterranean Sea. By feeding counterfeit signals to the ship, he was able to drive it far off course. All the time, the navigation system reported the vessel was moving calmly along its intended course. The same researcher also demonstrated the ability to spoof unmanned aerial vehicles (UAVs) The purpose of this paper is to demonstrate a navigation system that does not rely on GPS. The only sensor required is a digital camera. The system works by taking a photograph of the ground and georegistering it to a reference image or digital elevation model (DEM) with the GeoMI(tm) georegistration software. By transferring geospatial information from the DEM to the photo, the system calculates the position and orientation of the aircraft. The process is fast enough to perform in real time and suitable for use as a primary or backup navigation system for aircraft, UAVs, and cruise missiles. For nighttime navigation, the system could be extended to infrared or radar imagery. Experimental results show that navigation accuracies of 2 meters CE90 can be achieved.
2013 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)
Mark D Pritt Kevin J LaTourette
22609382
A novel fast and accurate algorithm for Terrain Referenced UAV localization
Recently, unmanned aerial vehicles (UAVs) have become one of the most popular and promising means for both military and civilian posts and academic research areas. Localization of the UAVs and persistent tracking of a UAV have vital importance to provide a UAV with navigation information and help to cope with getting lost permanently. Indeed, Inertial Navigation System (INS) and Global Positioning System (GPS) seem to be adequate for navigation of UAVs. However, an alternative augmented navigation system for UAVs should be taken into consideration since INS has accumulated errors and GPS always has the possibility of jamming and satellite signal loss. Terrain Referenced Navigation (TRN) could be a good alternative as a decision support system for these main systems. This study aims to detect the location of a lost or GPS disabled UAV throughout a planned flight by using only the terrain data. In addition, assumptions and limitations are minimized for the sake of simplifying the process to apply this methodology on a real UAV in the future, e.g. flight through all directions with physically possible turn rates is allowed. In order to provide data of the terrain, Digital Elevation Model (DEM) of the flight region with 30m resolution is exploited. The proposed method is based on searching and matching the collected elevation values of the terrain below UAV within the DEM and makes use of simulation techniques to test the accuracy and performance. The whole algorithm utilizes a sequence of elevation values with a predefined length (i.e. profile) Mainly, all possible profiles are generated before the flight and stored in a huge search space. We identify, sort and classify these elevation profiles in order to perform search operations in a small subset of the huge set. During the flight, a sequence of terrain elevations, which is computed with the help of radar and barometric altimeter measurements, is searched within a small neighborhood of corresponding profile set.
2013 International Conference on Unmanned Aircraft Systems (ICUAS)
Orhan Eroglu Guray Yilmaz
15270030
TRN history, trends and the unused potential
The term Terrain Referenced Navigation is used to describe a larger family of systems that estimate position by measuring terrain heights and comparing them with a digital elevation map. This is not a new navigation technique. In fact, TRN has been around for some time, with its history dating back to the 1950s. At that time the technological possibilities were rather limited, so forerunner terrain sensing systems were completely analog and/or would require the need of the human factor. With the "digital age" TRN methods started to become practical. The 70s and 80s were the decades which account for most of the development in this field. Different processing techniques settled into shape and TRN found practical application especially within military technology. Later on, the interest in terrain sensing methods started to diminish. Nowadays impressive technology exists. For example: laser sensors can measure terrain elevation with a signal having a milli radian beamwidth; digital maps of 1m resolution are available. These are not the only enablers that warrant a re investigation of the current potential of TRN. Among other factors we remind the current capabilities in: digital signal processing, real time computing power and data storage. Many of the previous limitations of TRN are no longer applicable and therefore this technique may once again be considered a strong candidate for accurate navigation solutions. This paper provides a look into TRN history and illustrates how a set of important developments in the past provide the basis for the (yet unused) potential of TRN for performance based navigation.
2012 IEEE/AIAA 31st Digital Avionics Systems Conference (DASC)
Dhadesugoor R Vaman