This paper studies the application of compact polarimetric (CP) SAR in the detection and identification of ocean internal solitary waves (ISWs). First, based on full-polarimetric ALOS PALSAR images, we construct CP SAR images and extract 26 CP features. Then, the ISWS-sea surface differentiation capability for the different polarization features is analyzed by using the Jeffries and Euclidean distances. The results show that [Math Processing Error]\lambda _{1} , Entropy ( [Math Processing Error]H ), Lambda, the polarimetric total power (Span) and the Stokes parameters (Stokesg0, and [Math Processing Error]Stokesg_{3} ) improve the ISWs detection results. On this basis, a k-means clustering algorithm based on CP features is introduced, and the results show that the ISWs detection and identification performance of the algorithm are superior to that of the traditional Wishart polarization clustering algorithm, which suggests that CP SAR has good application prospects in the detection and identification of ocean ISWs.

中文翻译：

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救灾中的 IT 挑战：我们从哈维飓风中学到了什么


本文研究了紧凑型极化（CP）SAR在海洋内孤立波（ISW）检测和识别中的应用。首先，基于全偏振ALOS PALSAR图像，构建CP SAR图像并提取26个CP特征。然后，利用杰弗里斯距离和欧氏距离分析了不同偏振特征下的ISWS-海面区分能力。结果表明：[数学处理误差]\lambda _{1}、熵([数学处理误差]H)、Lambda、极化总功率(Span)和斯托克斯参数(Stokesg0，以及[数学处理误差]Stokesg_{ 3} ) 改进 ISW 检测结果。在此基础上，提出了一种基于CP特征的k-means聚类算法，结果表明该算法的ISWs检测和识别性能均优于传统的Wishart偏振聚类算法，表明CP SAR具有良好的性能。在海洋ISWs检测与识别中的应用前景.