Detecting depolarized targets using a new geometrical perturbation filter

Abstract

Target detectors using polarimetry are often focused on single targets, since these can be characterized in a simpler and deterministic way. The algorithm proposed in this paper is aimed at the more difficult problem of partial target detection (i.e. targets with arbitrary degree of polarization). The authors have already proposed a single target detector employing filters based on a geometrical perturbation. In order to enhance the algorithm to the detection of partial targets, a new vector formalism is introduced. The latter is similar to the one exploited for single targets but suitable for complete characterization of partial targets. A new feature vector is generated starting from the covariance matrix, and exploited for the perturbation method. Validation against L-band fully polarimetric airborne E-SAR, and satellite ALOS-PALSAR data and X-band dual polarimetric TerraSAR-X data is provided with significant agreement with the expected results. Additionally, a comparison with the supervised Wishart classifier is presented revealing improvements