A new sequential Monte Carlo implementation of cardinality balanced multi-target multi-Bernoulli filter

doi:10.16383/j.aas.2016.c150182

	A new sequential Monte Carlo implementation of cardinality balanced multi-target multi-Bernoulli filter
	Chen, Hui 1,2; Han, Chong-Zhao 1
刊名	Zidonghua Xuebao/Acta Automatica Sinica
	2016
卷号	42 期号:1 页码:26-36
关键词	Distributed computer systems Distribution functions Iterative methods Monte Carlo methods Random variables Auxiliary variables Multi-Bernoulli Multi-target tracking Random finite set (RFS) Sequential Monte Carlo
ISSN号	02544156
DOI	10.16383/j.aas.2016.c150182
英文摘要	To improve the effectiveness of particle sampling in the sequential Monte Carlo (SMC) implementation of the multi-Bernoulli filter, this paper proposes a new SMC implementation of the CBMeMBer filter using the so called auxiliary particle filter (APF). First, according to the posterior multi-Bernoulli density, this paper redefines the sampling problem by introducing some auxiliary random variables suited to the CBMeMBer filter. The measurement and the prior density component are chosen accordingly as auxiliary variables. As a result, this method can sample particles concentrating on the high likelihood state space and the Bernoulli probability density of track corrected by the actual target measurement. Therefore, a more accurate posterior probability density of multi-target multi-Bernoulli (MeMBer) can be obtained. Meanwhile, the sampling distribution functions of those auxiliary random variables and the multi-target states are designed for the legacy tracks and the measurement-corrected tracks. Moreover, this paper corrects iteratively the prior density component based on the progressive correction (PC) algorithm in order to improve the solving accuracy of sampling distribution functions. Finally, simulation results show the effectiveness of the proposed approach as applied to two typical nonlinear tracking problems. Copyright © 2016 Acta Automatica Sinica. All rights reserved.
语种	中文
出版者	Science Press
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/112773]
专题	电气工程与信息工程学院
作者单位	1.Ministry of Education Key Laboratory for Intelligent Networks and Network Security, Xi'an Jiaotong University, Xi'an; 710049, China; 2.School of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou; 730050, China
推荐引用方式 GB/T 7714	Chen, Hui,Han, Chong-Zhao. A new sequential Monte Carlo implementation of cardinality balanced multi-target multi-Bernoulli filter[J]. Zidonghua Xuebao/Acta Automatica Sinica,2016,42(1):26-36.
APA	Chen, Hui,&Han, Chong-Zhao.(2016).A new sequential Monte Carlo implementation of cardinality balanced multi-target multi-Bernoulli filter.Zidonghua Xuebao/Acta Automatica Sinica,42(1),26-36.
MLA	Chen, Hui,et al."A new sequential Monte Carlo implementation of cardinality balanced multi-target multi-Bernoulli filter".Zidonghua Xuebao/Acta Automatica Sinica 42.1(2016):26-36.