| 一种基于独立联合K-分布CFAR的舰船检测算法 |
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| 引用本文： | 艾加秋,齐向阳,刘凡,石力.一种基于独立联合K-分布CFAR的舰船检测算法[J].中国科学院研究生院学报,2010,27(5):651-656. |
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| 作者姓名： | 艾加秋 齐向阳 刘凡 石力 |
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| 作者单位： | 1. 中国科学院电子学研究所,北京100190;中国科学院研究生院,北京,100049
2. 中国科学院电子学研究所,北京,100190 |
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| 摘 要： | 分析了中高分辨率SAR海洋图像的目标和海杂波特点. 利用舰船目标的灰度相关性和形状特性与背景杂波的差异,提出了一种基于独立联合K-分布CFAR的舰船检测算法. 算法建立了海杂波的二维独立联合K-分布概率模型,通过给定的虚警率得到检测阈值以对图像进行检测. 该算法能够极大地抑制斑点噪声和背景局部不均匀对检测带来的影响,有效地降低了虚警数,检测效果得到了明显改善.
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| 关 键 词： | 合成孔径雷达 舰船检测 恒虚警 独立联合K-分布 |
| 收稿时间： | 2009-10-27 |
| 修稿时间： | 2010-03-16 |
A new CFAR ship detection algorithm based on independent joint K-distribution |
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| AI Jia-Qiu,QI Xiang-Yang,LIU Fan,SHI Li.A new CFAR ship detection algorithm based on independent joint K-distribution[J].Journal of the Graduate School of the Chinese Academy of Sciences,2010,27(5):651-656. |
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| Authors: | AI Jia-Qiu QI Xiang-Yang LIU Fan SHI Li |
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| Institution: | 1. Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China;
2. Graduate University, Chinese Academy of Sciences, Beijing 100049, China |
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| Abstract: | In this paper, differences in the characteristic between target and clutter in medium and high resolution SAR images are analyzed. By considering the differences in gray intensity correlation and shape between the ship target and the clutter, a new ship CFAR detection algorithm is proposed based on 2D independent joint K-distribution. The joint gray intensity distribution using 2D independent joint K-distribution in the clutter is modeled in the algorithm, and the detecting threshold is calculated at a given probability of false alarm to detect the SAR images. With this algorithm, the false alarms caused by speckle and local background non-homogeneity can be greatly reduced, the detection performance is much improved. |
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| Keywords: | SAR ship detect CFAR 2D independent joint K-distribution |
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