组网无源雷达变数目多目标跟踪算法  

Multiple passive-radar based time-varying number targets tracking algorithm

作　　者：时银水[1,2] 姬红兵[1] 杨柏胜[1] 

机构地区：[1]西安电子科技大学电子工程学院,陕西西安710071 [2]防空兵指挥学院信息控制系,河南郑州450052

出　　处：《西安电子科技大学学报》2010年第2期218-223,共6页Journal of Xidian University

基　　金：国家自然科学基金资助项目(60677040;60871074)

摘　　要：针对组网无源雷达多目标跟踪问题,提出一种新的变数目多目标跟踪算法,实时估计目标数目与多目标状态.算法采用多站集中式融合策略解决无源观测的不完全性问题,采用最小二乘算法构造伪位置观测解决无源观测的非线性问题.针对变数目多目标跟踪问题,利用随机集理论将多目标状态与观测构成随机有限集,通过高斯混合概率假设密度滤波递归计算多目标状态随机有限集的后验强度,实时得到目标数目及其状态的估计.算法引进最小二乘算法估计出候选目标点进行数据关联,解决了无源观测线较近时无源数据关联精度下降问题.仿真实验验证了该算法的有效性.A new recursive algorithm is proposed for jointly estimating the time-varying number of targets and their states through passive radar measurements.Firstly,multi-sensor central fusion scheme is adopted to improve the weak observability for passive systems.Secondly,the least square method is embedded to calculate pseudo-location measurements by which the nonlinearity is solved.Thirdly,for the scenario of the time-varying target number,the new approach involves modeling the collections of targets and measurements as random finite sets（RFSs）,respectively,and applying the Gaussian mixture probability hypothesis density（GMPHD） recursion to propagate the posterior intensity,which is a first-order statistic of the random finite sets by which both the time-varying number and states of multiple targets could be estimated properly.Furthermore,data association is accomplished by all potential targets located by the least square algorithm,which could avoid the decrease of association reliability when lines of sight（LOS） from different targets are close to each other.Simulation results in a scenario of tracking targets through multiple passive sensors show the advantages of the proposed algorithm.

关 键 词：无源雷达 随机有限集 概率假设密度 多目标跟踪 数据关联 

分 类 号：TN953.5[电子电信—信号与信息处理]