A Novel Multiple Maneuvering Targets Tracking Algorithm with Data Association and Track Management

被引：9
|
作者：
Zhang, Shicang [1 ,2 ]
Li, Jianxun [1 ]
Wu, Liangbin [2 ]
机构：
[1] Shanghai Jiao Tong Univ, Shanghai 200240, Peoples R China
[2] AVIC Radar & Avion Inst, Wuxi 214063, Peoples R China
来源：
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS | 2013年 / 11卷 / 05期
关键词：
Data association and track management; generalized pseudo-Bayesian of first order; pseudo-measurement; HYPOTHESIS DENSITY FILTER; MIXTURE PHD FILTER; MULTITARGET TRACKING; PMHT; RADAR;
D O I：
10.1007/s12555-012-0177-z
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A novel multiple maneuvering targets tracking algorithm with data association and track management is presented in this paper. First, the variation of the generalized pseudo-Bayesian estimator of first order is designed. Then, the data association and track management via handling two matrices are given, which reflect the relationships between target trajectory and the output of the Gaussian mixture probability hypothesis density (PHD) filter for jump Markov system models (JMS-GM-PHD) filter. The tracking performance of the proposed algorithm is compared with two conventional algorithms. One is JMS-GM-PHD filter, the other is algorithm entitled hybrid algorithms for multi-target tracking using MET and GM-CPHD which is denoted as hybrid method hereinafter. The results of Monte Carlo simulation show that the proposed filter has overall performance than the conventional.
引用
收藏
页码：947 / 956
页数：10
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