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Multiple target tracking using particle filter based multi-scan joint probabilistic data association filter

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3 Author(s)
Liu Jing ; Sch. of Electron. & Inf. Eng., Xi'an JiaoTong Univ., Xi'an, China ; Han ChongZhao ; Hu Yu

In this paper, a particle filter based multi-scan JPDA filter is proposed to deal with the data association problem in multiple target tracking. In the proposed multi-scan JPDA algorithm, the distributions of interest are the marginal filtering distributions for each of the targets, and these distributions are approximated with particles. The multi-scan JPDA algorithm examines the joint association events in a multi-scan sliding window and calculates the marginal posterior probability based on the multi-scan joint association events. The proposed algorithm is illustrated via an example involving tracking of two slowly maneuvering targets based on resolved measurements.

Published in:

Control Conference (CCC), 2011 30th Chinese

Date of Conference:

22-24 July 2011

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