Rao-Blackwellized particle cardinality balanced multi-target multi-Bernoulli filter
Chen, Hui1,2; Han, Chong-Zhao1
2016-02-01
发表期刊Kongzhi Lilun Yu Yingyong/Control Theory and Applications
ISSN10008152
卷号33期号:2页码:146-153
摘要The multi-Bernoulli filter propagates approximately the multi-target posterior density so that solving target tracking problem and extracting target state based on random finite set are more tractable. Considering a state space model whose state can be divided into linear and nonlinear part, this paper analyzes the Rao-Blackwell theorem based filtering algorithm. Then, using the corresponding algorithm of decorrelation of state noises, we presents the filtering formula for linear state. Moreover, this paper proposes a Rao-Blackwellized particle cardinality balanced multi-target multi-Bernoulli filter. This algorithm firstly implements the particle filtering for multi-Bernoulli nonlinear state, and the filtering formula of multi-Bernoulli linear state is derived afterwards based on the nonlinear filtering result. The proposed filter can sample particle in a lower dimensional state space and improve the overall target tracking performance. The simulation results of the multi-target tracking show the effectiveness of the proposed approach. © 2016, Editorial Department of Control Theory & Applications South China University of Technology. All right reserved.
关键词Clutter (information theory) Distributed computer systems Monte Carlo methods Set theory State space methods Multi-Bernoulli Multi-target tracking Particle filter Random finite sets Rao-Blackwell
DOI10.7641/CTA.2016.50588
收录类别EI
语种中文
出版者South China University of Technology
EI入藏号20161702304865
EI主题词Target tracking
EI分类号716.1 Information Theory and Signal Processing - 921 Mathematics - 921.4 Combinatorial Mathematics, Includes Graph Theory, Set Theory - 922.2 Mathematical Statistics
来源库Compendex
分类代码716.1 Information Theory and Signal Processing - 722.4 Digital Computers and Systems - 921 Mathematics - 921.4 Combinatorial Mathematics, Includes Graph Theory, Set Theory - 922.2 Mathematical Statistics
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文献类型期刊论文
条目标识符https://ir.lut.edu.cn/handle/2XXMBERH/112980
专题电气工程与信息工程学院
作者单位1.Ministry of Education Key Lab for Intelligent Networks and Network Security, Xi'an Jiaotong University, Xi'an; Shaanxi; 710049, China;
2.School of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou; Gansu; 730050, China
第一作者单位兰州理工大学
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Chen, Hui,Han, Chong-Zhao. Rao-Blackwellized particle cardinality balanced multi-target multi-Bernoulli filter[J]. Kongzhi Lilun Yu Yingyong/Control Theory and Applications,2016,33(2):146-153.
APA Chen, Hui,&Han, Chong-Zhao.(2016).Rao-Blackwellized particle cardinality balanced multi-target multi-Bernoulli filter.Kongzhi Lilun Yu Yingyong/Control Theory and Applications,33(2),146-153.
MLA Chen, Hui,et al."Rao-Blackwellized particle cardinality balanced multi-target multi-Bernoulli filter".Kongzhi Lilun Yu Yingyong/Control Theory and Applications 33.2(2016):146-153.
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