A Radar Multi-target Tracking Algorithm Based on Gaussian Mixture PHD Filter under Doppler Blind Zone

Wei Qiang; Liu Zhong

doi:10.12000/JR16125

Volume 6 Issue 1

Apr. 2017

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LIU Pingyu, LYU Xiaode, LIU Zhongsheng, et al. Research on co-channel interference suppression method for passive radar based on the jiont processing of primary and reference channels[J]. Journal of Radars, 2020, 9(6): 974–986. doi: 10.12000/JR19047

Citation:

Wei Qiang, Liu Zhong. A Radar Multi-target Tracking Algorithm Based on Gaussian Mixture PHD Filter under Doppler Blind Zone[J]. Journal of Radars, 2017, 6(1): 34-42. doi: 10.12000/JR16125

Citation:

Wei Qiang, Liu Zhong. A Radar Multi-target Tracking Algorithm Based on Gaussian Mixture PHD Filter under Doppler Blind Zone[J]. Journal of Radars, 2017, 6(1): 34-42. doi: 10.12000/JR16125

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A Radar Multi-target Tracking Algorithm Based on Gaussian Mixture PHD Filter under Doppler Blind Zone

DOI: 10.12000/JR16125

Wei Qiang^{①,②
,
,},
Liu Zhong^{①
,}

①.
Electronics Engineering College,Naval University of Engineering,Wuhan 430033,China
②.
Air Force Early Warning Academy,Wuhan 430019,China

Funds: The National Ministries Foundation

Received Date: 2016-11-10
Rev Recd Date: 2017-01-10

Available Online: 2017-03-15

Publish Date: 2017-02-28

Abstract

Abstract

Due to the Doppler Blind Zone (DBZ), the target tracking of Doppler radar becomes more and more complicated. In this paper, a multi-target tracking algorithm based on Gaussian Mixture Probability Hypothesis Density (GM-PHD) for DBZ is proposed. The algorithm introduces the Minimum Detectable Velocity (MDV) information to the traditional detection probability model to update the GM-PHD and the updated equation of the GM-PHD is deduced. The simulation results show that, compared to the traditional GM-PHD with the only Doppler measurement, the proposed algorithm improves greatly the radar tracking performance of moving target under the condition of minor MDV.

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References(19)

References

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