组网无源雷达变数目多目标跟踪算法

doi:10.3969/j.issn.1001-2400.2010.02.007

Abstract

Abstract:

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.

Key words: passive radar, random finite sets, probability hypothesis density(PHD), multiple targets tracking, data association

SHI Yin-shui;JI Hong-bing;YANG Bai-sheng. Multiple passive-radar based time-varying number targets tracking algorithm[J].J4, 2010, 37(2): 218-223.

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

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