Discrimination of civilian vehicles using wide-angle SAR

At high frequencies, synthetic aperture radar (SAR) imagery can be represented as a set of points corresponding to scattering centers. Using a collection of sequential azimuths with a fixed aperture we build a cube of points for each of seven civilian vehicles in the Gotcha public release data set (GPRD). We present a baseline study of the ability to discriminate between the vehicles using strictly 2D geometric information of the scattering centers. The comparison algorithm is independent of pose and translation using a novel application of the partial Hausdorff distance (PHD) minimized through a particle swarm optimization. Using the PHD has the added benefit of reducing the effects of occlusions and clutter in comparing vehicles from pass to pass. We provide confusion matrices for a variety of operating parameters including azimuth extent, various amplitude cutoffs, and various parameters within PHD. Finally, we discuss extension of the approach to near-field imaging and to additional point attributes, such as 3D location and polarimetric response.