Volume 3 Number 7 (Jul. 2008)
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JCP 2008 Vol.3(7): 23-30 ISSN: 1796-203X
doi: 10.4304/jcp.3.7.23-30

Interacting Multiple Model Particle-type Filtering Approaches to Ground Target Tracking

Ronghua Guo1, Zheng Qin2, Xiangnan Li2, and Junliang Chen2
1Department of Computer Science & Technology, Tsinghua University, Beijing, China
2School of Software, Tsinghua University, Beijing, China


Abstract—Ground maneuvering target tracking is a class of nonlinear and/or no-Gaussian filtering problem. A new interacting multiple model unscented particle filter (IMMUPF) is presented to deal with the problem. A bank of unscented particle filters is used in the interacting multiple model (IMM) framework for updating the state of moving target. To validate the algorithm, two groups of multiple model filters: IMM-type filters and particle-type multiple model filters, are compared for their capability in dealing with ground maneuvering target tracking problem. Simulation shows that particle-type filters outperform IMM-type filters in the estimate accuracy and the IMMUPF method relatively has much better performance than the IMMPF method.

Index Terms—particle filter, unscented particle filter (UPF), interacting multiple model (IMM), ground target tracking

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Cite: Ronghua Guo, Zheng Qin, Xiangnan Li, and Junliang Chen, "Interacting Multiple Model Particle-type Filtering Approaches to Ground Target Tracking," Journal of Computers vol. 3, no. 7, pp. 23-30, 2008.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat,etc
E-mail: jcp@iap.org
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