On the superresolution identification of observables from swept-frequency scattering data

A superresolution signal processing algorithm is used for the identification of wavefronts from the fields scattered from several canonical targets. Particular wave objects that are examined are single and multiple edge diffraction, scattering from flat and curved surfaces, cone diffraction, and creeping waves. The scattering data are computed numerically via the method of moments (MoM) and are processed using a modified matrix-pencil algorithm. General properties of superresolution processing of such data-independent of the particular algorithm used-are assessed through an examination of the Cramer-Rao (C-R) bounds for basic scattering scenarios.