Simulation Study, Based On Ground-based Radar Data Processing And Resource Scheduling

X-band Ground Based Radar(GBR) plays an important role in National Missile Defense(NMD) system, it has many important functions such as middle stage surveillance and interception , trajectory prediction, target identifying and classifying. It has important significance to analyze and study GBR system, not only for ballistic missile'attack and defense research, but also for our national space surveillance and ballistic missile defense system development.In this dissertation, the Data Process(DP) subsystem and Radar Control Program(RCP) subsystem of GBR simulation system have been studied and discussed.The main work and innovation of this dissertation is as follows:(1) Track filter, the basic element of track system, has been researched. We analyze the advantage and disadvantage of common target kinematic model such as constant velocity model, constant acceleration model, Noval statistic model. Meanwhile we researchα-β–γfilter, Kalman filter and extend Kalman filter. Based on the requirement of GBR simulation system, we adopt extend Kalman filter algorithm of ballistic missile model.(2) Data association method of multi-target tracking has also been researched. We study the distance-gate which has big effect on data association, analyze global distance-gate and elliptical distance-gate. Then we adopt different distance-gate according to different trajectory state. Finally we analyze common data association algorithm such as nearest neighbor algorithm,probability data association algorithm and joint probability data association algorithm and adopt the nearest neighbor algorithm in our simulation system.(3) Adaptive sample algorithm such as predicted covariance threshold method, pre-establish sample interval method, and recursive method have been researched. We especially analyze the advantage and disadvantage of predicted covariance threshold method and pre-establish sample interval method, and present an improved pre-establish sample interval method.(4) We analyze adaptive schedule policy and factors affecting resource schedule...