Improved Sar Target Detection Using Subspace Filtering

Abstract

We propose a new class of Subspace filter based algorithms for detecting targets in forest clutter environment. The training phase of the proposed SAR target detection algorithms “learns” the clutter characteristics using local or global clutter subspaces. Both off-line and on-the-fly self-training versions of the algorithm are presented. These adaptive… (More)

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