Ship Detection in GF-3 NSC Mode SAR Images
Liu Zeyu① Liu Bin①* Guo Weiwei① Zhang Zenghui① Zhang Bo② Zhou Yueheng② Ma Gao② Yu Wenxian①
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)
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.
Key words ： GF-3 satellite
Synthetic Aperture Radar (SAR)
Ship detection
Pixel classification
Received: 2017-06-15;
Published: 2017-08-18
Fund: Key Program of National Natural Science Foundation of China-High Resolution SAR Database and Data Quality Evaluation (61331015)
Cite this article:
Liu Zeyu,Liu Bin,Guo Weiwei et al. Ship Detection in GF-3 NSC Mode SAR Images[J]. JOURNAL OF RADARS, 2017, 6(5): 473-482.
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2017, Vol. 6 
