Statistical target behaviour in SAR images

The paper discusses the statistical behaviour of targets in synthetic aperture radar (SAR) images and demonstrates how this information can be exploited for automatic SAR target classification and recognition. It describes a target-smoothing algorithm for estimating the underlying radar cross-section, which can be used with an appropriate noise model to generate many target realisations for a given imaging configuration. This allows a statistical analysis of target features to be performed that can be used to enhance feature-based classification, as is demonstrated by a simple classification experiment using real targets