Target Tracking Based on Particle Filtering in Passive Sensor Array

Li Liang-qun; Huang Jing-xiong; Xie Wei-xin

doi:10.3724/SP.J.1146.2008.00201

Volume 31 Issue 4

Dec. 2010

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Li Liang-qun, Huang Jing-xiong, Xie Wei-xin. Target Tracking Based on Particle Filtering in Passive Sensor Array[J]. Journal of Electronics & Information Technology, 2009, 31(4): 844-847. doi: 10.3724/SP.J.1146.2008.00201

Citation:

Li Liang-qun, Huang Jing-xiong, Xie Wei-xin. Target Tracking Based on Particle Filtering in Passive Sensor Array[J]. Journal of Electronics & Information Technology, 2009, 31(4): 844-847. doi: 10.3724/SP.J.1146.2008.00201

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Target Tracking Based on Particle Filtering in Passive Sensor Array

doi: 10.3724/SP.J.1146.2008.00201

Received Date: 2008-02-20
Rev Recd Date: 2008-07-25
Publish Date: 2009-04-19

Abstract

Abstract

In this paper, a new Multiple Model Rao-Blackwellized Particle Filter (MMRBPF) based algorithm is proposed for maneuvering target tracking in passive sensor array. The advantage of the proposed approach is that the Rao-Blackwellization allows the algorithm to be partitioned into target tracking and model selection sub-problems, where the target tracking can be solved by the extend Kalman filter, and the model selection by multiple model Rao-Blackwellized particle filter. The analytical relationship between target state and model is exploited to improve the efficiency and accuracy of the proposed algorithm. Finally, a nonlinear measurement model of multiple passive sensors is founded. The simulation results show that the proposed algorithm results in more accurate tracking than the IMM (Interacting Multiple Model) method.

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References

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