Passive Location Tracking Technology

With the development of electronic technology, anti-radiation techniques and anti-probe techniques also have a great improvement. A lot of emphasize is put on this realm because the passive radar meets the needs of these developments.The basic work of the passive radar is to determine the position and the speed of the targets within the noisy circumstance. The main contents of this paper will be introduced as following:1,The principle of passive localization is described. The article does some test on target according to some different parameters and compares the results gotten by different detection errors. The definition of CRLB and GDOP is also introduced.2,Discussed four methods for joint positioning by different combinations of three measured parameters. The basic principles of four positioning methods were introduced, and the positioning simulation experiments were carried out. The simulation results of the joint location and the result got by using a single parameter were compared to analyze whether the joint location method can improve location accuracy.3,The paper studied the basic principle of passive tracking and introduced the theory and computational procedures of EKF algorithm in detail. The tracking on the target was simulated several times by different measure parameters and the results were analyzed in the end.4,This paper studied the particle filter algorithm and probability hypothesis density algorithm which are developed rapidly in recent years. Particle filter's basic principles and operational procedures are described and its improved algorithm which is called EKPF algorithm is explained deeply. We also make some comparison on the simulation results of the tracking system that gotten by EKF algorithm and EKPF algorithm separately. Then it introduces the PHD algorithm which is a new and effective method on multi-target tracking problem. Because of the difficulty to achieve the PHD algorithm's requirements, an implementation algorithm based on the particle algorithm is introduced. PHD filtering algorithm has great potential because it is an effective way to avoid the traditional data association problem on target tracking.