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      Ship Detection in GF-3 NSC Mode SAR Images

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          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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          Author and article information

          Journal
          Journal of Radars
          Chinese Academy of Sciences
          01 October 2017
          : 6
          : 5
          : 473-482
          Affiliations
          [1 ] ①(Shanghai Key Laboratory of Intelligent Sensing and Recognition, Shanghai Jiao Tong University, Shanghai 200240, China)
          [2 ] ②(China Academy of Space Technology-Xi’an, Xi’an 710100, China)
          Article
          804eb6578d5d41d8ae8c065293b30e7e
          10.12000/JR17059

          This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

          Categories
          Technology (General)
          T1-995

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