Multi-Angular Sar Scattering Anisotropy Analysis Based on Low-Rank Matrix Decomposition

Multi-angular SAR can be used to obtain the information of target scattering characteristics at different aspect angles. The scattering anisotropy extraction attracts more attention but the method is not much. And because of background noise, the anisotropy extraction based on aspect entropy is not good. Low-rank matrix decomposition is widely used in the change detection process of SAR images. The most important thing is that it can distinguish the strong point target from the background image and the sparse matrix obtained by decomposition eliminates the sidelobe noise of the target. In this paper, firstly we proposed the application of low-rank matrix decomposition to multi-angular SAR images to analyze the scattering characteristics and then the coefficient of variation is used to validate and quantify the anisotropy of the target in the scene after low-rank matrix decomposition. The anisotropy quantization result is less affected by noise than aspect entropy. The Gotcha X-band circular SAR data is used to validate the method. ¹