Detection and Analysis of Anisotropic Scattering in SAR Data

Scattering from man-made objects in SAR imagery exhibits aspect and frequency dependencies which are not well modeled by standard SAR imaging techniques. If ignored, these deviations will reduce recognition performance due to the model mismatch, but when appropriately accounted for, these deviations from the ideal point scattering model can be exploited as attributes to better distinguish scatterers and their respective targets. With this premise in mind, we have developed an efficient modeling framework that incorporates scatterer anisotropy. One of the products of our analysis is the assignment of an anisotropy label to each scatterer conveying the degree of anisotropy. Anisotropic behavior is commonly predicted for geometric scatterers (scatterers with a simple geometric structure), but it may also arise from volumetric scatterers (random arrangements of interfering point scatterers). Analysis of anisotropy arising from these two modalities shows a clear source-dependent relationship between the anisotropy classification and parameters of the scatterer. In particular, the degree of anisotropy is closely related to the size of the scatterer, and increasing the aperture size reduces the incidence of volumetric anisotropy but preserves the detection rate for geometric anisotropy. This result helps to address the question in the SAR community regarding the utility of wide-aperture SAR data for ATR since wide-aperture data reveals geometric anisotropy while resolving volumetric anisotropy into individual isotropic scatterers.