Identifiability of 3D Attributed Scattering Features from Sparse Nonlinear Apertures

Attributed scattering feature models have shown potential in aiding automatic target recognition and scene visualization from radar scattering measurements. Attributed scattering features capture physical scattering geometry, including the non-isotropic response of target scattering over wide angles, that is not discerned from traditional point scatter models. In this paper, we study the identifiability of canonical scattering primitives from complex phase history data collected over sparse nonlinear apertures that have both azimuth and elevation diversity. We study six canonical shapes: a flat plate, dihedral, trihedral, cylinder, top-hat, and sphere, and three flight path scenarios: a monostatic linear path, a monostatic nonlinear path, and a bistatic case with a fixed transmitter and a nonlinear receiver flight path. We modify existing scattering models to account for nonzero object radius and to scale peak scattering intensities to equate to radar cross section. Similarities in some canonical scattering responses lead to confusion among multiple shapes when considering only model fit errors. We present additional model discriminators including polarization consistency between the model and the observed feature and consistency of estimated object size with radar cross section. We demonstrate that flight path diversity and combinations of model discriminators increases identifiability of canonical shapes.