Research On Group Targets Tracking For MIMO HF Sky-wave Radar With Array Error And Interferences

HF sky-wave radars utilize the refraction mechanism of ionosphere to achieve the over-the-horizon detection for the targets with very long distance.However,the multimode propagation effects of the ionosphere can cause undesired noise interference at the receiving end of th e high-frequency sky-wave radar,known as multimode interference,t he multi-mode interference signal and the target echo signal sometimes have the same delay and the radar distance,which causes the direction of the target wave to be indistinguishable.The multiinput multi-output(MIMO)radar can effectively mitigate the effects of this multi-mode interference and has been applied in the sky-wave radar.Firstly,the MIMO sky-wave radar echo signal model is introduced,and the simulation and analysis of the MUSIC spectrum of the MIMO received signal proves the effectiveness of the MIMO system radar in comparison with the traditional radar in ionospheric multi-mode interference suppression.Secondly,the conventional Capon beamforming interference suppressi on technology is introduced,and an improved Capon beamforming interference suppression method based on compression covariance sensing(CCS)is proposed for the problems existing in the conventional Capon beamforming method.This algorithm can effectively avoid the main beam distortion problems of the Capon beamforming method and increase the output signal to interference plus noise ratio.Then,for the problem that the CCS has poor suppression of main-lobe interference,the main-lobe interference suppression method based on Matching Projection(MP)is further introduced,and it is combined with the method based on CCS to perform joint interference suppression on the received echo signals,and a beam space-wise DOA estimation method is used to estimate the angle used for subsequent tracking after interference suppression.Finally,the group target tracking method based on extended Kalman and particle filter after interference suppression is introduced.Based on the prior information that requires the known number of targets in the tracking area and does not change with time and the complex data association algorithm is needed,this paper further introduces the Gaussian Mixture-Probability Hypothesis Density(GM-PHD)filter tracking algorithm.Finally,considering the uncertainty and diversity of the target motion model,the GM-PHD group target tracking based on multiple models was studied,the simulation results show that the tracking effect of the multi-model method when tracking intense maneuvering targets is much better than that using single model tracking.