An automatic K-Wishart distribution ship detector for PolSAR data

Weiwei Fan, Feng Zhou, Mingliang Tao, Xueru Bai
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引用次数: 3

Abstract

This paper presents an automatic ship detection algorithm for polarimetric synthetic aperture radar (PolSAR) data. Based on the non-Gaussian K-Wishart distribution model for complex backscattering coefficients, the PolSAR image is clustered automatically by a modified expectation maximization algorithm. A goodness-of-fit test is incorporated to improve the model fitness of the cluster iteratively. Then, the SPAN of ship cluster center is used to detect ships. Finally, the experimental results of a real measured UAVSAR dataset show that the proposed algorithm could improve the ability of weak target detection while reduces the rate of false alarm and miss detections.
用于PolSAR数据的自动K-Wishart分布船舶探测器
提出了一种基于偏振合成孔径雷达(PolSAR)数据的船舶自动检测算法。基于复杂后向散射系数的非高斯K-Wishart分布模型,采用改进的期望最大化算法对PolSAR图像进行自动聚类。采用拟合优度检验迭代提高聚类的模型适应度。然后,利用聚类中心的SPAN对舰船进行检测;最后,在UAVSAR实测数据集上的实验结果表明,该算法可以提高弱目标检测能力,降低虚警和漏检率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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