Research On Target Tracking Techniques Based On Passive Radar

Active radar is difficult to effectively solve the problems from electronic jamming,stealth technology,anti-radiation attacks,low-altitude and ultra-low-altitude raid,passive radar has greater advantages in face of these four threats because of its different work way,has become an important part of modern electronic reconnaissance system.However,the positioning accuracy of passive radar is not high,the track start is difficult and the tracking trajectory is not continuous in the target tracking process.In view of this,this thesis focuses on the target tracking technology of passive radar,and the main work includes as following:Firstly,for the data preprocessing problem in the centralized tracking system,it is possible to effectively reduce the number of false combinations and the amount of computation in the tracking process by using the angle measurements from multi-station to associate and forming the matching pairs based on target's position before tracking process,and simulating the geometric dilution of precision(GDOP)as the correlation errors under different station rules.Furthermore,the nonlinear filter algorithm in target tracking is studied.The simulation results show than the Unscented Kalman filter(UKF)has advantages over the extended Kalman filter(EKF)in the passive radar tracking process.Secondly,for single target continuous trajectory tracking,the IMM_UKF algorithm combined by the interacting multiple model(IMM)algorithm and the UKF algorithm is studied.The simulations experiments illustrate that the position estimation error and the velocity estimation error,which estimated by IMM_UKF with Doppler information,are smaller than the ones estimated only by angle measurements.Aim at the single target tracking segment associate(TSA)problem,two sequential correlation algorithm based on 'forward prediction and backward estimation(FP-BE)' or 'forward estimation and backward prediction(FE-BP)' are proposed.Compared with the traditional weighted correlation method and sequential correlation method,the proposed algorithm improves the tracking performance and the target's estimation accuracy.The simulation results verify the correctness and effectiveness of the proposed algorithm.Thirdly,aiming at the multi-target tracking problem,the method of tracking start based on intuition is studied to reduce the number of false trajectories in track processing,and the joint probabilistic data association(JPDA)algorithm is studied to solve the correlate issue between the target trajectories and the measurement data.Furthermore,two multi-target tracking sequence correlation algorithm based on FP-BE or based on FEBP are proposed to solve the problem of multi-target TSA,by using the state estimation in the fix time to sequential correlate,to solve multi-target TSA within the threshold time,and to increase the correlation accuracy.The simulation results verify the correctness and effectiveness of these proposed algorithm.