Research On Single Observer Passive Location Algorithm

The passive location technology has great significance in enhancing the system's stability in complicated electromagnetic environment because the detection system works without electromagnetic radiation and has long detection distantce. Due to these advantages, the passive location technology has broad application prospects in many fields, such as rescuing on the sea, the location of radar signal of radio and television, fire control system on the target's location tracking, electronic reconnaissance and targeting, monitoring and control of space vehicles, GPS. Single observer passive location is the technology that the detection system determine the target state through a single observer measures the information of radiation sources. Therefore, its system is much simpler and more flexible, and aslo can work without multiple stations, data transmission and communication between different stations, when compared with multiple stations passive location. All makes the passive location technology becoming a research focus.The essence of passive location technology is the combination of locationing method and algorithm. Locationing method and algorithm are the key points of passive location technology , which determine the location precision and rapidity. Therefore, we studied the phase change rate location method with several different filtering algorithms, and focused the filtering algorithms as chief research object. The major tasks are as follow:(1) Simply introduced the persent development situation and the key technology of single observer passive location technology.(2) We studied the principle of location of radiation with fixed position to moved single observer by using phase change rate method. The position equation and position error equation was derivated, and computer simulation was applied to analyse the error contour. In addition, we studied the bearings-only and its changing rate method, transforming of location coordinate, and also compare the positon errors which obtained by bearings-only method and phase change rate method in the same simulations condition.(3) Several different filtering methods were studied in this dissertation. In practical application, passive location is a nonlinear problems because of the noise. Searching a filtering location method with small location error, higher precision and stability is an important research topic in single observer passive location technology. Thus, we studied the extended kalman filtering (EKF) algorithm, extended kalman particle filtering (EPF) algorithm, modified gain extended kalman filtering (MGEKF) algorithm, which all based on phase change rate method, and deduced the filtering gain equations, filtering state update equations and filtering covariance update equations. The dissertation did numerous computer simulations to analyse the performance of these filtering algorithms.(4) The application of genetic algorithm in passive location technology. In order to overcome the filter divergence and local optimal solution of traditional filtering algorithm in actual application, a new single observer passive location method base on genetic algorithm was proposed in this dissertation, and feasibility of the algorithm was proved by numerous simulations. According to the simulations, the performance of the genetic algorithm was proved much better in location stability and real-time aspects than traditional filtering algorithm.