Radar Target Joint Detection And State Estimation

In the information processing technology,weak targets and multi-target detection and state parameter estimation under low signal-to-noise ratio(SNR)condition have been the technical problems of radar and other sensor devices.From the perspective of radar detection information processing,radar detection faces the “four low problems” of low SNR,low data rate,low resolution and low measurement dimension,and the potential information loss in data processing.From the practical significance,in the face of stealth aircraft,space debris,small spacecraft and other types of threats,detecting long-range targets as early as possible,the state estimation,cataloging and tracking become the primary tasks of radar.In the face of the problem of radar detection,the cost of improving hardware performance is huge,the technology is difficult to break through,and the transceiver means is difficult to achieve,and then information processing technology has become an important means of radar detection.In order to improve the performance of weak target and multi-target detection and state parameter estimation,a general Bayesian filter based on random finite set(RFS)which called joint detection tracking algorithm on signal processing is proposed to deal with the problem of radar information processing.The main work is as follows:Firstly,aiming at the problems of weak target detection and state estimation,multitarget detection and state estimation,instead of detecting weak target by the traditional SNR threshold algorithm and detecting multi-target by the hypothesis correlation algorithm,this paper presents a kind of joint detection tracking algorithm,namely general Bayesian filter based on random finite set for moving target detection and state estimation.Then,the detection and state estimation methods of single weak target in the radar measurement background are studied.At the signal processing level,the radar observation and target state models are constructed by formal Bayesian modeling.The single-target Bernoulli filter is used to simulate the research problem,and the single weak target detection and state parameter estimation are realized.Simulation results show that the performance of the proposed algorithm is superior to that of the target detection and state estimation under low SNR.At last,the multi-target detection and state estimation methods in radar measurement background are studied.The radar observation and target state models are analyzed and constructed by formal Bayesian modeling,and the problem is simulated by CPHD filter to realize multi-target detection and state parameter estimation.Simulation results show that the performance of the proposed method is superior to that of the target detection and state parameter estimation under the multi-objective condition.Detection and state measurement are the basic tasks of all radars.Detection range and measurement accuracy are important indicators for evaluating radar performance.In this paper,Bayesian filtering method based on random finite set is used to improve the performance of weak targets and multi-targets detection and state parameter estimation under radar measurement,so as to enhance the radar performance and increase the radar detection range.