Research On Multi-Sensor Embattling And Continious Tracking Technique Applying For Anti-Stealth And Anti-Interference

Highly maneuverable target locating and tracking under anti-stealth and anti-interference environment is a challenging subject. Part of measurements of single sensor will be lost in traditional interference or target stealth technology. Multi-sensor target tracking is a paradigm of information fusion technique dealing with target tracking problem. It estimates target state through intelligent integration of multi-sensor data to gain better tracking performance than single sensor does. So it is significant in theory and practical in application to research on how to make use of the redundant and complement information of multi-sensor for object locating and tracking continually, accurately.In this thesis, the methods of single station radar netting optimize embattle techniques, multi-sensor target locating and tracking fusion, track fitting and tracing on blind area are mainly researched with the background of one project that cooperates with certain department of China Aerospace Science & Industry Company.Main contents and results are as follow:First, an approach to radar netting to solve the problem of how optimally to locate the different radars is proposed to achieve a satisfactory surveillance area and some highly-concerned areas inside as well as the ability of anti-stealth and anti interference in some degree. Based on the RCS of the interested targets and the coverage diagrams of the radars, the performance distribution in the surveillance area is analyzed, and a mathematical model for radar netting optimization along with some strategies in the netting algorithm is presented. The approach also takes several factors into account, such as local terrain around radar, man-made interference, stealth target, flying direction of target, track information known previously and so on. Genetic algorithm is introduced to solve the complexity of finding the best result. Simulation experiment illustrates the validity of the approach.Second, multi-station fusion locating and tracking algorithms under the simulate background provide by first part are researched. in order to get high location precision in most of areas, assembled optimum location algorithm is presented by combining full information location, bearing only location and range only location algorithms, and least square optimization is used for each algorithm to improve precision. based on EKF algorithms, and central fusion structure is selected for tracing. It can solve observability and nonlinear problems when tracing by bearing-only measures. Another algorithms locating first then taking the location data as measure of the KF input is presented. The EKF and KF is based on Current Statistical Model. The simulation experiment is conducted for the case which consists of twenty stations. The result shows that the EKF tracking performances are satisfied comparing with the KF.Finally, a creative method based on above research is presented for highly maneuvering target tracking and applying under three dimension and blind area circumstance, which is based on segmenting track identifier. Simulation results show that under the circumstance of tracking highly maneuvering targets, comparing with the existence methods this algorithm has a better performance.