Performances of polarimetric subspace SAR processors for target detection and interference rejection

We develop a new Synthetic Aperture Radar (SAR) algorithm based on physical models for the detection of a Man-Made Target (MMT) embedded in strong interferences. These physical models for the MMT and the interferences are integrated in low-dimension subspaces. Our SAR algorithm consists of applying the oblique projection of the received signal into the target subspace along the interference one. We apply our algorithms to FoPen (Foliage Penetration) detection. Its performances are better compared to those obtained with previous SAR algorithms: the MMT detection is highly improved and the interferences are strongly rejected. We also study the robustness of our new SAR algorithm to interference modeling errors. Finally, we present results on real data.