Performances of Polarimetric Subspace SAR Processors for Target Detection and Interference Rejection
The authors 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. The authors' SAR algorithm consists of applying the oblique projection of the received signal into the target subspace along the interference one. They apply their 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. They also study the robustness of their new SAR algorithm to interference modeling errors. Finally, they present results on real data.