SAR Automatic Target Recognition based on Slow Feature Analysis

This paper presents a new Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) method based on slow feature analysis. Slow feature analysis (SFA) is a method for learning invariant or slowly varying features from multi-dimensional input signal. The SFA-based SAR ATR system does not require any pre-processing, such as filtering or pose estimation of the image. The performance of the method is evaluated via three classification experiments on Moving and Stationary Target Acquisition and Recognition (MSTAR) database. The experiment results show the effectiveness of the proposed method on SAR ATR problem.