AN IMPROVED NONPARAMETRIC CFAR METHOD FOR SHIP DETECTION IN SINGLE POLARIZATION SYNTHETIC APERETUER RADAR IMAGERY

被引：5

作者：

Tian, S. R. ^{[1
]}

Wang, C. ^{[2
]}

Zhang, H. ^{[2
]}

机构：

[1] Nanjing Univ Sci & Technol, Sch Elect & Opt Engn, Dept Elect Engn, Nanjing 210094, Jiangsu, Peoples R China

[2] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Beijing 100094, Peoples R China

来源：

2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2016年

基金：

中国国家自然科学基金;

关键词：

Ship detection; synthetic aperture radar (SAR); kernel density estimation (KDE); constant false alarm rate (CFAR);

D O I：

10.1109/IGARSS.2016.7730733

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this letter, an improved kernel density estimation (KDE) constant false alarm rate (CFAR) method is proposed for ship detection in single polarization synthetic aperture radar (SAR) images. The proposed method consists of a target enhancement filter, an adaptive KDE bandwidth estimation method and an improved KDE-CFAR. The gravity-based target enhancement filter is utilized to remove the inhomogeneity in SAR images, and thereby meet the requirement of the KDE bandwidth estimation method. The proposed method provides an automatic training sample selection scheme, avoiding the manual intervention in conventional method. In addition, the KDE-CFAR is improved, employing the exponential function as the kernel since it provides an analytical solution for the CFAR criterion, which is unavailable for the Gaussian kernel. Experimental results with six spaceborne SAR images demonstrated that the proposed method is effective and efficient for ship detection application.

引用

页码：6637 / 6640

页数：4

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