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No description available.

The Kalman filter algorithm can be applied as a recursive estimator of the state of a dynamic system described by a linear difference equation. Given discrete measurements linearly related to the state of the system, but corrupted by white Gaussian noise, the Kalman filter estimate of the system is statistically optimal with respect to a quadratic function of the estimate error. The first objective of this paper is to give deep enough insight into the mathematics of the Kalman filter algorithm to be able to choose the correct type of algorithm and to set all the parameters correctly in a basic application. This description also includes several examples of different approaches to derive and to explain the Kalman filter algorithm. In addition to the mathematical description of the Kalman filter algorithm this paper also provides an implementation written in MATLAB. The objective of this part is to correctly replicate the target tracker used in the surveillance radar PS-90. The result of the implementation is evaluated using a simulated target programmed to have an aircraft-like behaviour and done without access to the actual source code of the tracker in the PS-90 radar

Thesis (M.S.)--Rochester Institute of Technology, 1991. / Typescript. Includes bibliographical references (p. 117-121).

As a result of recent technological advances in modernized sensor sets and sensor platforms, sensor management combined with sensor platform path planning are studied to conduct intelligence, surveillance and reconnaissance (ISR) operations in novel ways. This thesis addresses the path planning and sensor management for aerial vehicles to cover areas of interest (AOIs), scan objects of interest (OOIs) and/or track multiple detected targets in surveillance missions. The problems in this thesis, which include 1) the spatio-temporal coordination of sensor platforms to observe AOIs or OOIs, 2) the optimal sensor geometry and path planning for localization and tracking of targets in a mobile three-dimensional (3D) space, and 3) the scheduling of sensors working in different (i.e., active and passive) modes combined with path planning to track targets in the presence of jammers, emerge from real-world demands and scenarios. The platform path planning combined with sensor management is formulated as optimization problems with problem-dependent performance evaluation metrics and constraints. Firstly, to cover disjoint AOIs over an extended time horizon using multiple aerial vehicles for persistent surveillance, a joint multi-period coverage path planning and temporal scheduling, which allows revisiting in a single-period path, is formulated as a combinatorial optimization with novel objective functions. Secondly, to use a group of unmanned aerial vehicles (UAVs) cooperatively carrying out search-and-track (SAT) in a mobile 3D space with a number of targets, a joint path planning and scanning (JPPS) is formulated based on the predictive information gathered from the search space. The optimal 3D sensor geometry for target localization is also analyzed with the objective to minimize the estimation uncertainty under constraints on sensor altitude, sensor-to-sensor and sensor-to-target distances for active or passive sensors. At last, to accurately track targets in the presence of jammers broadcasting wide-band noise by taking advantage of the platform path planning and the jammer's information captured by passive sensors, a joint path planning and active-passive scheduling (JPPAPS) strategy is developed based on the predicted tracking performance at the future time steps in a 3D contested environment. The constraints on platform kinematic, flyable area and sensing capacity are included in these optimization problems. For these multisensor path planning and decision making, solution techniques based on the genetic algorithm are developed with specific chromosome representations and custom genetic operators using either the non-dominated sorting multiobjective optimization (MOO) architecture or the weighted-sum MOO architecture. Simulation results illustrate the performance and advantage of the proposed strategies and methods in real-world surveillance scenarios. / Thesis / Doctor of Philosophy (PhD)

Thesis (Ph. D.)--University of Texas at Austin, 2006. / Vita. Includes bibliographical references.

<p> A new radar tracking detector using fixed delay lines in place of continuously variable delay lines is described. The fixed delays are switched in and out depending on the output of a correlator. Results of a working system are shown using bang-bang feedback and analog-to-digital feedback, for tracking a time-varying delay. </p> / Thesis / Master of Engineering (MEngr)

International Telemetering Conference Proceedings / October 25-28, 1999 / Riviera Hotel and Convention Center, Las Vegas, Nevada / The NASA GSFC’s Wallops Flight Facility’s (WFF) Mobile Range Control System (MRCS) is based on the functionality of the WFF Range Control Center at Wallops Island, Virginia. The MRCS provides real time instantaneous impact predictions, real time flight performance data, and other critical information needed by mission and range safety personnel in support of range operations at remote launch sites. The MRCS integrates a PC telemetry processing system (TELPro), a PC radar processing system (PCDQS), multiple Silicon Graphics display workstations (IRIS), and communication links within a mobile van for worldwide support of orbital, suborbital, and aircraft missions. This paper describes the MRCS configuration; the TELPro’s capability to provide single/dual telemetry tracking and vehicle state data processing; the PCDQS’ capability to provide real time positional data and instantaneous impact prediction for up to 8 data sources; and the IRIS’ user interface for setup/display options. With portability, PC-based data processing, high resolution graphics, and flexible multiple source support, the MRCS system is proving to be responsive to the ever-changing needs of a variety of increasingly complex missions.

Cross-eye jamming is an Electronic Attack (EA) technique that induces an angular error in the radar being jammed. The main benefit of cross-eye jamming is that it is effective against monopulse tracking radars, which are largely immune to other forms of jamming. The objective of this research is to gain a complete understanding of cross-eye jamming so that systems that might be developed in future can be properly specied. The main contribution of this work is a comprehensive mathematical and experimental study of retrodirective cross-eye jamming. The mathematical analysis considers all aspects of an isolated, single-loop, retrodirective cross-eye jamming engagement, thereby avoiding the approximations inherent in other cross-eye jamming analyses. Laboratory experiments that accurately represent reality by using the radar for both transmission and reception, and simulating a true retrodirective cross-eye jammer were performed to validate the theoretical analysis. Lastly, the relationship between the angular error induced in the radar being jammed and the matching required from a cross-eye jammer system is explored. The most important conclusion of this work is that the traditional analyses of cross- eye jamming are inaccurate for the conditions under which cross-eye jammers operate. These inaccuracies mean that the traditional analyses are overly conservative, particularly at short ranges and for high cross-eye gains, suggesting that practical cross-eye jammers can be realised more easily than is generally believed. / Thesis (PhD)--University of Pretoria, 2010. / Electrical, Electronic and Computer Engineering / unrestricted