ABSTRACT
This chapter introduces several approaches for obtaining building features. In literature, there is consensus that building features can be more reliably extracted using an approach exploiting scatterer models. The result is a measurement model in which the output vector is of higher dimension than the input vector. This yields an underdetermined system, and extraction of the building features needs to be performed based on sparse representation algorithms. Point target focusing, smashed filtering, and use of an overcomplete dictionary are three different approaches that use inversion for obtaining building features. The chapter explains the implementation based on the backscatter models for canonical scatterer. In point scattering focusing, the applied matched filters are based on point scatterers for obtaining the representation. Focused radar images of building interiors may be obtained by point scattering focusing, such as in conventional synthetic aperture radar techniques.
