<title>Some results from scattering-based tomography for HRR and SAR prediction</title>

Abstract

The problem of predicting HRR radar and SAR signal magnitudes based on a limited number of observations is a challenging component of feature aided tracking. In this paper we describe the application of a scattering-based tomographic technique that builds persistent scatterer models of ground vehicles from a collection of HRR and/or SAR observations from varying look angles. Results are obtained using MSTAR data. Target detection results are shown using ROC curves and compared with nearest observation matching. Application of these techniques to the move-stopmove problem of vehicle tracking is also described.