Volume 10 Issue 1
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CUI Xingchao, SU Yi, and CHEN Siwei. Polarimetric SAR ship detection based on polarimetric rotation domain features and superpixel technique[J]. Journal of Radars, 2021, 10(1): 35–48. doi: 10.12000/JR20147
Citation: CUI Xingchao, SU Yi, and CHEN Siwei. Polarimetric SAR ship detection based on polarimetric rotation domain features and superpixel technique[J]. Journal of Radars, 2021, 10(1): 35–48. doi: 10.12000/JR20147
shu

Polarimetric SAR Ship Detection Based on Polarimetric Rotation Domain Features and Superpixel Technique

doi: 10.12000/JR20147

  • The State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information, Changsha 410073, China

Funds:  The National Natural Science Foundation of China (61771480), The Natural Science Foundation of Hunan Province (2020JJ2034), The Youth Talents Project of Hunan Province (2019RS2025), The Equipment Pre-Research Foundation (61404160109), The Key Research Projects of National University of Defense Technology (ZK18-02-14)
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  • Corresponding author: CHEN Siwei, chenswnudt@163.com
  • Received Date: 2020-12-19
  • Rev Recd Date: 2021-02-02
    • Available Online: 2021-02-22
  • Publish Date: 2021-02-25
    Abstract
  • Sea surveillance is an important application of polarimetric Synthetic Aperture Radar (SAR), but ship detection in dense areas remains a major challenge. Due to the crosstalk of multiple targets in dense ship areas, it can be difficult to collect pure sea clutter samples for threshold determination when using the traditional Constant False Alarm Rate (CFAR) moving window, which decreases the detection performance. To address this issue, in this paper, a polarimetric SAR ship detection method is proposed based on polarimetric rotation domain features and superpixel technique, with consideration of both feature selection and detector design. For feature selection, the backscattering of radar targets is sensitive to the relative geometry between the target orientations and the radar line of sight. The information hidden in this scattering diversity can be mined using polarimetric rotation domain analysis, from which the polarimetric correlation pattern and a set of polarimetric rotation domain features are obtained. Target-to-Clutter Ratio (TCR) analysis is conducted, and the three polarimetric features with the highest TCR values are selected for successive target detection. On this basis, a clutter superpixel selection method is developed for detector design based on K-means clustering, which effectively circumvents the influence of dense ship targets on near sea clutter. CFAR ship detection results can be obtained based on the selected clutter samples. Experimental studies on spaceborne Radarsat-2 and GaoFen-3 full polarimetric SAR datasets indicate that, the proposed method can effectively detect dense ship targets with 95% higher figures of merit.

     

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