Volume 9 Issue 4
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LIU Chao, SUN Jinping, CHEN Xiaolong, et al. Random finite set-based extended target tracking method with amplitude information[J]. Journal of Radars, 2020, 9(4): 730–738. doi: 10.12000/JR19071
Citation: LIU Chao, SUN Jinping, CHEN Xiaolong, et al. Random finite set-based extended target tracking method with amplitude information[J]. Journal of Radars, 2020, 9(4): 730–738. doi: 10.12000/JR19071
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Random Finite Set-based Extended Target Tracking Method with Amplitude Information

DOI: 10.12000/JR19071
  • 1.

    School of Electronic and Information Engineering, Beihang University, Beijing 100191, China

  • 2.

    PLA 92853 Unit, Huludao 125106, China

  • 3.

    Naval Aviation University, Yantai 264001, China

Funds:  The National Natural Science Foundation of China (61471019, U1633122)
More Information
  • Corresponding author: SUN Jinping, sunjinping@buaa.edu.cn
  • Received Date: 2019-07-25
  • Rev Recd Date: 2019-10-26
    • Available Online: 2019-11-26
  • Publish Date: 2020-08-28
    Abstract
  • The random finite set-based extended target tracking methods generally partition measurements by spatial information. It is possible to place clutter measurements into target cells in a dense clutter environment resulting in degradation of tracking performance. To solve this issue, in this paper, the amplitude information of the target and clutter was introduced into the Gaussian Inverse Wishart Probability Hypothesis Density (GIW-PHD) filter, and thus, the optimal partition was found by calculating the amplitude likelihood of the measurement cells. Additionally, when calculating the centroid of a measurement cell, amplitude was used as a weighting factor to find the mass center instead of the widely used geometric center. This further reduced clutter interference. The tracking results of Swerling 1 fluctuating targets in a Rayleigh clutter when the signal-to-clutter ratios were 13 dB and 6 dB showed that the performance of the proposed algorithm in cardinality estimation and state estimation was better than that of the GIW-PHD filter.

     

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