Research On Macro-micro Resource Management Technology For Phased Array Radar Based On Tracking-feedback

Recently, sensor resource management technology is a research focus to dealwith complex battlefield environment and has a stupendous significance to improvethe comprehensive performance of the sensor system. In the framework of resourcemanagement control based on feedback, this dissertation has studied the problem ofthe micro-management of multi-target tracking by phased array radar andmacro-management of multi-sensor distribution, according to the sensor managementof the macro/micro two-level model.First of all, resource management control framework, based on trackingperformance feedback, has been established by combining with the concept offeedback control.Secondly, to solve the problem of management of multi-target tracking byphased array radar, two sensor resource management algorithms have been provided:1) steady resource management algorithm of multi-target tracking by phased arrayradar based on Riccati equation and2) dynamic resource management algorithm ofmulti-target tracking by phased array radar based on covariance. Both of thealgorithms have been tested by simulation.Thirdly, to solve the problem of multi-sensor allocation in radar networks, threemulti-sensor allocation algorithms of different tracking performance have beenintroduced:1) dynamic multi-sensor allocation algorithm in radar networks based oninformation gain and2) dynamic multi-sensor allocation algorithm in radar networksbased on covariance and3) dynamic multi-sensor allocation algorithm in radarnetworks based on cost function.Then, two kinds of fast multi-sensor allocation algorithms named the fastmulti-sensor allocation algorithm in radar networks based on information gain and thefast multi-sensor allocation algorithm in radar networks based on the outline Riccatiequation have been proposed to improve the speed of multi-sensor allocationalgorithms. By introducing an appropriate searching strategy, out-line optimizationand online selection methods significantly improve the efficiency of the algorithmswhile keeping the tracking accuracy at a high level.Finally, this thesis proposed a compensational method for distributed radar networks to solve the problem of losing information with target tracking in distributedradar networks. Its effectiveness has been tested by simulation.