Matched subspace detectors for discrimination of targets from trees in SAR imagery

Abstract

We investigate the use of subspace-based detectors for discriminating vehicles from trees in low frequency synthetic aperture imagery. We model tree scattering as structured isotropic interference responses and model dominant vehicle scattering as dihedral responses. We form linear subspaces of tree and target responses, and apply subspace-based detection methods developed by Scharf and Friedlander (1994). Analysis on synthetic tree and target models show the viability of this approach. Preliminary results on measured imagery provide lower performance, suggesting the need for improved data calibration and improved scattering models of trees at low frequencies.