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CLC number: TN911.72
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 0000-00-00
Cited: 14
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Using interacting multiple model particle filter to track airborne targets hidden in blind Doppler
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DU Shi-chuan, SHI Zhi-guo, ZANG Wei, CHEN Kang-sheng. Using interacting multiple model particle filter to track airborne targets hidden in blind Doppler[J]. Journal of Zhejiang University Science A, 2007, 8(8): 1277-1282.
@article{title="Using interacting multiple model particle filter to track airborne targets hidden in blind Doppler",
author="DU Shi-chuan, SHI Zhi-guo, ZANG Wei, CHEN Kang-sheng",
journal="Journal of Zhejiang University Science A",
volume="8",
number="8",
pages="1277-1282",
year="2007",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2007.A1277"
}
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%A ZANG Wei
%A CHEN Kang-sheng
%J Journal of Zhejiang University SCIENCE A
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%@ 1673-565X
%D 2007
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2007.A1277
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T1 - Using interacting multiple model particle filter to track airborne targets hidden in blind Doppler
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A1 - CHEN Kang-sheng
J0 - Journal of Zhejiang University Science A
VL - 8
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SP - 1277
EP - 1282
%@ 1673-565X
Y1 - 2007
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.2007.A1277
Abstract: In airborne tracking, the blind Doppler makes the target undetectable, resulting in tracking difficulties. In this paper, we studied most possible blind-Doppler cases and summed them up into two types: targets’ intentional tangential flying to radar and unintentional flying with large tangential speed. We proposed an interacting multiple model (IMM) particle filter which combines a constant velocity model and an acceleration model to handle maneuvering motions. We compared the IMM particle filter with a previous particle filter solution. Simulation results showed that the IMM particle filter outperforms the method in previous works in terms of tracking accuracy and continuity.
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