Feature Detection of Sea-surface Small Targets via Relative Sample Entropy in Frequency Domain
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1.Nanjing University of Information Science and Technology 2.Nanjing Xinda Institute of Safety and Emergency Management;2.Nanjing University of Information Science and Technology;3.Nanjing marine radar institute

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The National Natural Science Foundation of China (General Program, Key Program, Major Research Plan)

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    Abstract:

    It has always been a difficult subject for marine radar to detect small targets on sea surface. To overcome the low detection probability of traditional detectors, a feature detector based on relative sample entropy (denoted as FD-RSE) is proposed in this paper. Firstly, the whitened spectrum is defined to suppress the main clutter region, thus enlarging the irregularity of the sea clutter sequence. Then, by introducing sample entropy describe the complexity of sea clutter sequence, relative sample entropy is extracted from whitened spectrum to serve as feature. Therefore, the difference between the geometric characteristic of sea clutter and that of target echo can be thoroughly exploited in the Doppler spectrum. Finally, the superiority of the proposed FD-RSE detector over traditional detectors in improving detection performance can be verified by the IPIX measured dataset.

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History
  • Received:March 02,2022
  • Revised:September 30,2022
  • Adopted:October 11,2022
  • Online:
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