Volume 11 Issue 3
Jun.  2022
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Article Navigation >  Journal of Radars  > 2022  >  11(3): 408-417
AN Mengyun, YIN Jiapeng, HUANG Jiankai, et al. Adaptive spectral polarization filter design for dual-polarization weather radar[J]. Journal of Radars, 2022, 11(3): 408–417. doi: 10.12000/JR21199
Citation: AN Mengyun, YIN Jiapeng, HUANG Jiankai, et al. Adaptive spectral polarization filter design for dual-polarization weather radar[J]. Journal of Radars, 2022, 11(3): 408–417. doi: 10.12000/JR21199
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Adaptive Spectral Polarization Filter Design for Dual-polarization Weather Radar

DOI: 10.12000/JR21199

  • State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, National University of Defense Technology, Changsha 410073, China

Funds:  The National Natural Science Foundation of China (61971429, 62171447), Postdoctoral International Exchange Program (48132), Science and Technology Innovation Program of Hunan Province (2020RC2042), The Scientific Research Program of the National University of Defense Technology (ZK21-25)
More Information
  • Corresponding author: YIN Jiapeng, yinjiapeng@nudt.edu.cn
  • Received Date: 2021-12-06
  • Accepted Date: 2022-01-25
  • Rev Recd Date: 2022-01-21
    • Available Online: 2022-01-29
  • Publish Date: 2022-03-08
    Abstract
  • This paper proposes an adaptive filtering method called the Adaptive Moving spectral Depolarization Ratio (AMsDR) filter to mitigate the clutter for dual-polarization weather radar based on Jensen-Shannon divergence principle. Specifically, the spectral depolarization ratio in the range-Doppler domain is the main variable distinguishing precipitation from clutter. The AMsDR filter can remove the clutter and noise and retain precipitation based on the difference of the spectral polarization feature and the spectral continuity of precipitation and clutter. The AMsDR filter can adaptively select the filter threshold depending on the echo difference between precipitation and clutter in different azimuths. Thus, the performance of the proposed filter is better than that of the current methods.

     

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