A Polarimetric Extension of Low-Rank Plus Sparse Decomposition and Radon Transform for Ship Wake Detection in Synthetic Aperture Radar Images

In past research, the problem of obtaining stable motion estimation of maritime targets in sea clutter making wake structure detection and reconnaissance difficult has been tackled. This new research presents an upgrade for automatic estimation of maritime target motion parameters by evaluating the generated Kelvin waves detected in synthetic aperture radar (SAR) images. The algorithm consists in considering the polarimetric (Pol) information of SAR images and evaluating a multiple-channel and dual-stage Pol low-rank plus sparse decomposition (Pol-LRSD) assisted by Radon transform (RT) for clutter reduction, sparse object detection, precise wake inclination estimation, and targets classification. This upgraded algorithm is based on Pol robust principal component analysis (Pol-RPCA) implemented by convex programming. This upgraded Pol-LRSD algorithm permits the extrapolation of the Pol signature of sparse objects of interest consisting of the maritime targets and the Kelvin pattern from the unchanging low-rank background. Pol-RPCA and RT methods applied to Pol SAR surveillance permit more precise detection and segmentation of maritime targets.