Feature Extraction using Attributed Scattering Center Models on SAR Imagery

We present algorithms for feature extraction from complex SAR imagery. The features parameterize an attributed scattering center model that describes both frequency and aspect dependence of scattering centers on the target. The scattering attributes extend the widely-used point scattering model, and characterize physical properties of the scattering object. We present two feature extraction algorithms, an approximate maximum likelihood method that relies on minimization of a nonlinear cost function, and a computationally faster method that avoids the nonlinear minimization step. We present results of applying both algorithms on synthetic model data, on XPatch scattering predictions of the SLICY test target, and on measured X-band SAR imagery.