Target decomposition and recognition from wide-angle SAR imaging based on a Gaussian amplitude-phase model

Abstract

Wide-angle synthetic aperture radar (W-SAR) imaging accounts for multi-azimuthal scattering and is feasible for retrieving more comprehensive features of complex targets. Because a typical target is seen as composed of its components (typically, some simple geometric objects), a Gaussian amplitude-phase (GAP) model has been developed for the analysis of multi-azimuthal scattering from these objects. Based on the time-frequency analysis of wide-angle scattering, the parameters of the GAP model were estimated, including the Gaussian variance, the surface curvature, and the number of objects in all imaged pixels. Numerical simulations and real measurements demonstrate the capability of the GAP model for decomposing and recognizing complex electric-large targets.