Research On Multi-station Passive Location And Tracking Algorithm Based On TDOA/AOA

Nowadays,because the complexity of electromagnetic environment is increasing,and the electronic countermeasure technology is constantly developing and maturing,How to locate and track the radiation source of enemy target accurately,timely and covertly in electronic warfare becomes the key to gain the first chance in the battlefield.Therefore,passive location and tracking technology become a very important technology in electronic warfare.Based on the Angle of Arrival(AOA)and Time Differences of Arrival(TDOA)localization system,this paper introduces jointing TDOA and AOA localization system and algorithm,and carry out some relevant researches aiming at some problems in practical application.Firstly,this paper introduces the basic models of TDOA localization system and AOA localization system.For the purpose of complementing the advantages of the two models,the TDOA-AOA localization model is introduced,and in this paper,the fomula of TDOA-AOA localization model's geometrical dilution of precision(GDOP)is derived.Based on the above content,two closed-form algorithms for the joint localization model are introduced.Secondly,aiming at the disadvantage that the traditional pseudo-linear closed-form algorithms are prone to threshold effects when the error increases,which leads to the sharp deterioration of the positioning accuracy,a location technique based on the salp swarm algorithm(SSA)is proposed.The SSA simulates the prodation process of the salp swarm,intelligently searches the observation space and gives the estimation solution based on the maximum likelihood principle,it can improves the threshold effects effectively.In addition,this paper improves the original SSA according to the characteristics of multi-station passive localization model.The simulation results show that the improved salp swarm algorithm(ISSA)can greatly enhance the ability of random search in the early stage,while maintaining the group convergence ability,and further improves the locating accuracy.Moreover,this paper studies the problem of ambiguity positioning which is easy to appear in the practical application of multi-observation localizaiton system.For the ambiguity problem of AOA localization,this paper studies the ambiguity point elimination problem of wideband noise FM signal.In the case that multiple signals are mixed and the arrival time cannot be distinguished,a method of calculating time difference information by the autocorrelation characteristics of signals is given,which can effectively solve the problem of eliminating ambiguity points in such cases.Furthermore,as for location ambiguity in TDOA localization,this paper analyses the situation of multiple ambiguous TDOA caused by mismatching of high repetition frequency signals,and proposes a method based on the different characteristics of motion patterns between ambiguous points and real target.The proposed method tracks all estimated points,including ambiguous points and real target,to estimate these velocity information.At last,we eliminate the ambiguous points by judging the speed of the estimated points.Finally,a non-common-view target tracking problem is studied in this paper.Because of obstacle occlusion in observation space or relative motion between the emitter and the observations,the emiter sometimes can not be observed simultaneously by all observations.At this time,due to the lack of information,the trace of target cannot be tracked correctly in the traditional sense.In this paper,the change of measurement informations in the non-common-view environment is analyzed in detail,and aiming at the tracking problem under this condition,the process noise covariance matrix is used to balance the trust of the predicted values,so that a more stable estimation result can be obtained in the weak observation interval.Through simulation results and theoretical analysis,it is proved that the method can effectively solve the tracking problem in non-consensus scenes.