CLC number: TP391
On-line Access: 2014-06-06
Received: 2014-01-25
Revision Accepted: 2014-04-03
Crosschecked: 2014-05-04
Cited: 3
Clicked: 8234
Tong-yang Jiang, Mei-qin Liu, Xie Wang, Sen-lin Zhang. An efficient measurement-driven sequential Monte Carlo multi-Bernoulli filter for multi-target filtering[J]. Journal of Zhejiang University Science C, 2014, 15(6): 445-457.
@article{title="An efficient measurement-driven sequential Monte Carlo multi-Bernoulli filter for multi-target filtering",
author="Tong-yang Jiang, Mei-qin Liu, Xie Wang, Sen-lin Zhang",
journal="Journal of Zhejiang University Science C",
volume="15",
number="6",
pages="445-457",
year="2014",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.C1400025"
}
%0 Journal Article
%T An efficient measurement-driven sequential Monte Carlo multi-Bernoulli filter for multi-target filtering
%A Tong-yang Jiang
%A Mei-qin Liu
%A Xie Wang
%A Sen-lin Zhang
%J Journal of Zhejiang University SCIENCE C
%V 15
%N 6
%P 445-457
%@ 1869-1951
%D 2014
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.C1400025
TY - JOUR
T1 - An efficient measurement-driven sequential Monte Carlo multi-Bernoulli filter for multi-target filtering
A1 - Tong-yang Jiang
A1 - Mei-qin Liu
A1 - Xie Wang
A1 - Sen-lin Zhang
J0 - Journal of Zhejiang University Science C
VL - 15
IS - 6
SP - 445
EP - 457
%@ 1869-1951
Y1 - 2014
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.C1400025
Abstract: We propose an efficient measurement-driven sequential Monte Carlo multi-Bernoulli (SMC-MB) filter for multi-target filtering in the presence of clutter and missing detection. The survival and birth measurements are distinguished from the original measurements using the gating technique. Then the survival measurements are used to update both survival and birth targets, and the birth measurements are used to update only the birth targets. Since most clutter measurements do not participate in the update step, the computing time is reduced significantly. Simulation results demonstrate that the proposed approach improves the real-time performance without degradation of filtering performance.
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