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Received: 2007-03-26

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Journal of Zhejiang University SCIENCE A 2007 Vol.8 No.10 P.1588~1595


An unscented particle filter for ground maneuvering target tracking

Author(s):  GUO Rong-hua, QIN Zheng

Affiliation(s):  Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China

Corresponding email(s):   grh05@mails.tsinghua.edu.cn

Key Words:  Interacting multiple model (IMM), Unscented particle filter (UPF), Ground target tracking, Particle filter (PF)

GUO Rong-hua, QIN Zheng. An unscented particle filter for ground maneuvering target tracking[J]. Journal of Zhejiang University Science A, 2007, 8(10): 1588~1595.

@article{title="An unscented particle filter for ground maneuvering target tracking",
author="GUO Rong-hua, QIN Zheng",
journal="Journal of Zhejiang University Science A",
publisher="Zhejiang University Press & Springer",

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%T An unscented particle filter for ground maneuvering target tracking
%A GUO Rong-hua
%A QIN Zheng
%J Journal of Zhejiang University SCIENCE A
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%DOI 10.1631/jzus.2007.A1588

T1 - An unscented particle filter for ground maneuvering target tracking
A1 - GUO Rong-hua
A1 - QIN Zheng
J0 - Journal of Zhejiang University Science A
VL - 8
IS - 10
SP - 1588
EP - 1595
%@ 1673-565X
Y1 - 2007
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2007.A1588

In this study, an unscented particle filtering method based on an interacting multiple model (IMM) frame for a Markovian switching system is presented. The method integrates the multiple model (MM) filter with an unscented particle filter (UPF) by an interaction step at the beginning. The framework (interaction/mixing, filtering, and combination) is similar to that in a standard IMM filter, but an UPF is adopted in each model. Therefore, the filtering performance and degeneracy phenomenon of particles are improved. The filtering method addresses nonlinear and/or non-Gaussian tracking problems. Simulation results show that the method has better tracking performance compared with the standard IMM-type filter and IMM particle filter.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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