基于频域相对样本熵的海面小目标特征检测
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1.南京信息工程大学 2.南京信大安全应急管理研究院;2.南京信息工程大学;3.南京船舶雷达研究所

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国家自然科学基金项目(面上项目,重点项目,重大项目)


Feature Detection of Sea-surface Small Targets via Relative Sample Entropy in Frequency Domain
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Affiliation:

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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    摘要:

    海面小目标一直是海洋雷达探测的重难点对象。针对传统检测器检测概率低的问题,本文提出了一种基于相对样本熵的特征检测器(Feature Detector via Relative Sample Entropy, FD-RSE)。首先,定义了白化频谱,实现对主杂波带的抑制,从而增大了海杂波序列的不规则性。其次,通过引入样本熵描述序列的复杂度,提取了白化频谱的相对样本熵,并将之作为特征。在检测时,该特征能够充分利用海杂波和含目标回波在频谱上的几何差异性。最后,IPIX实测数据验证表明:与传统检测器相比,FD-RSE检测器能有效改善检测性能。

    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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历史
  • 收稿日期:2022-03-02
  • 最后修改日期:2022-09-30
  • 录用日期:2022-10-11
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