Research On Passive Cross-Positioning Method Based On Unscented Kalman Filter

Along with the continuous development of technology,traditional active positioning technology has been unable to satisfy the requirement of modern target positioning.Relying on the advantages of high concealment and long operating distance,passive positioning technology has been widely concerned by experts and scholars.Among them,cross-positioning is widely used due to the small number of observation stations and fast positioning speed.However,with the increasingly complex positioning scenarios,how to achieve efficient target positioning under the premise of low-cost and multi-scenario is worth further research.Aiming at the problem of locating static single target,dynamic single target and dynamic multitarget,a passive cross-positioning method which is based on unscented Kalman filter and a small number of observation stations is proposed.Meanwhile,this method realizes the accurate location of targets in different moving states.The main research contents of this paper are as follows:1.To solve the problem of static single target positioning,a cross-positioning algorithm of mobile single station based on unscented Kalman filter is designed.Firstly,the passive crosspositioning model of mobile single station is established.Then the observability of mobile single station positioning system is analyzed,and the optimal path planning of mobile station is proposed.Eventually,combined with the concept of relative motion,the positioning of static single base station is equivalent to that of fixed single station to uniformly moving target.Then,a cross-positioning algorithm of mobile single station based on unscented Kalman filter is designed,and the feasibility of this method is verified by simulations and experiments.2.For the dynamic single target cross-positioning problem,a dynamic single target crosspositioning algorithm based on unscented Kalman filter is designed.Firstly,by analyzing the principle of two-stations cross-positioning,the dynamic single target cross-positioning model of mobile two-stations is established.Then the time calibration method of measuring data of two-stations is studied when it is used for positioning.Finally,a dynamic single target crosspositioning algorithm based on unscented Kalman filter is designed.Results of simulation and experiment show the feasibility and effectiveness of this method in dynamic single target crosspositioning.3.Aiming at the dynamic multitarget positioning problem,a multitarget location tracking algorithm based on unscented Kalman filter is designed.The dynamic multitarget crosspositioning model of mobile two-stations is firstly established.Then,aiming at the problem of misalignment caused by gate overlap in traditional target association algorithms,an optimal target association method based on nearest neighbor classification is proposed.Finally,a multitarget tracking algorithm based on unscented Kalman filter is designed.The feasibility and effectiveness of this method in dynamic multitarget cross-positioning is confirmed by simulation and experiment results.