The Sensor Path Optimization Technology In Complex Tracking Environment

Under the background of increasingly accumulated modern war,it is very important to improve the performance of target tracking in complex environment.Mobile radar base station can effectively solve this problem.However,the problem of measurement uncertainty caused by target missing and clutter interference further enhances the difficulty of sensor path optimization in complex tracking environment.In this thesis,the sensor path optimization problem in complex tracking environment is discussed under the framework of target tracking method based on data association.The main research contents and innovations are as follows:(1)The sensor path optimization method based on minimizing the trace of CRLB in ideal environment is studied and deduced in depth.Firstly,the sensor path optimization model is constructed by combining partially observable Markov decision process,and the objective cost function of sensor path optimization based on CramerRao lower bound is designed.Secondly,under the premise of satisfying the motion constraints of the sensor itself,the motion control instruction of the sensor is solved to minimize the cost function.Finally,the real-time optimization of sensor path is realized;Finally,the real-time performance and effectiveness of the proposed optimization method are verified by optimizing the sensor paths of different measurement systems.(2)The target track recognition technology with unknown true value in complex tracking environment is proposed.In the complex tracking environment,due to the missing target detection,clutter interference,and the limitation of the tracking algorithm itself,the tracking algorithm still outputs a certain number of unknown identity tracks.In the absence of the true value of the target state reference,this paper studies the target track recognition technology based on target measurement false track.Firstly,the target measurement sequence is extracted from the historical measurement information obtained by the sensor and used as the true value of the target in the measurement domain;Then,the output track set of the tracking algorithm is converted to the measurement domain,and the true value of the target in the measurement domain is assisted to identify the track of the tracking target.Finally,in different measurement systems,the effectiveness of the proposed method for identifying target tracks in complex environments is fully verified.This method can not only provide target track information for sensor path optimization in complex tracking environment,but also provide true value reference for performance evaluation of different tracking methods.(3)The sensor path optimization technology based on traditional data association framework in complex tracking environment is proposed.Firstly,IPDA algorithm is used to realize automatic target tracking in complex tracking environment.Then,the target track is identified from the unknown identity track output by IPDA algorithm,and the sensor path optimization objective function is constructed by using the target track information,and the motion path of the sensor is solved.Finally,the target tracking accuracy and track management performance of the proposed method in complex tracking environment are fully verified in different measurement systems.