Performance Analysis of Internal Solitary Wave Detection and Identification Based on Compact Polarimetric SAR

Abstract

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 $\lambda _{1} $ , Entropy ( $H$ ), Lambda , the polarimetric total power ( Span ) and the Stokes parameters ( Stokesg 0, and $Stokesg_{3}$ ) 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.