Volume 6 Issue 5
Oct.  2017
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Article Navigation >  Journal of Radars  > 2017  >  6(5): 473-482
Liu Zeyu, Liu Bin, Guo Weiwei, Zhang Zenghui, Zhang Bo, Zhou Yueheng, Ma Gao, Yu Wenxian. Ship Detection in GF-3 NSC Mode SAR Images[J]. Journal of Radars, 2017, 6(5): 473-482. doi: 10.12000/JR17059
Citation: Liu Zeyu, Liu Bin, Guo Weiwei, Zhang Zenghui, Zhang Bo, Zhou Yueheng, Ma Gao, Yu Wenxian. Ship Detection in GF-3 NSC Mode SAR Images[J]. Journal of Radars, 2017, 6(5): 473-482. doi: 10.12000/JR17059
shu

Ship Detection in GF-3 NSC Mode SAR Images

DOI: 10.12000/JR17059
  • ①.

    Shanghai Key Laboratory of Intelligent Sensing and Recognition, Shanghai Jiao Tong University, Shanghai 200240, China

  • ②.

    China Academy of Space Technology-Xi’an, Xi’an 710100, China

Funds:  Key Program of National Natural Science Foundation of China—High Resolution SAR Database and Data Quality Evaluation (61331015)
  • Received Date: 2017-06-15
  • Rev Recd Date: 2017-07-31
    • Available Online: 2017-08-18
  • Publish Date: 2017-10-28
    Abstract
  • GF-3, the first C-band full-polarimetric Synthetic Aperture Radar (SAR) satellite with a space resolution up to 1 m, has multiple strip and scan imaging modes. In this paper, we propose a maritime ship detection algorithm that detects ship targets via pixel classification in a Bayesian framework and employ effective enhancement methods to improve detection performance based on the data characteristics. We compare and analyze the results of detection experiments using the proposed algorithm with those of several Constant False Alarm Rate (CFAR) algorithms. The experimental results verify the effectiveness of the proposed algorithm.

     

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