Models of anisotropic scattering for 3D SAR reconstruction

We study different modeling approaches to anisotropic scattering from man-made objects to derive novel solutions to the 3D imaging problem from multi-pass circular synthetic aperture radar measurements. We first consider sub-aperture methods that segment the measurements in the azimuth domain and reconstruct the scene by solving the regularized inverse problem. We propose an algorithm that jointly solves the imaging problem over multiple neighboring views by imposing joint sparsity in the spatial domain and group sparsity in the height dimension. Next, we propose a method that solves the problem over the entire aperture by exploiting the sparsity of dominant scattering centers in the scene and approximating the scattering coefficients using Gaussian basis functions in the azimuth domain. Finally, we compare the proposed approaches with conventional sparsity-based approaches on a dataset comprising of civilian vehicles.