CLC number: TP24; TP31
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 0000-00-00
Cited: 4
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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",
volume="8",
number="10",
pages="1588-1595",
year="2007",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2007.A1588"
}
%0 Journal Article
%T An unscented particle filter for ground maneuvering target tracking
%A GUO Rong-hua
%A QIN Zheng
%J Journal of Zhejiang University SCIENCE A
%V 8
%N 10
%P 1588-1595
%@ 1673-565X
%D 2007
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2007.A1588
TY - JOUR
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
Abstract: 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.
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