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Radar target recognition using structured sparse representation is the focus of this paper. Block-sparse representation and recovery is applied to the radar target recognition problem assuming a stepped-frequency radar is used. The backscatter of commercial aircraft models as recorded in a compact range is used to train and test a block-sparse based classifier. The motivation is to investigate scenarios where the target backscatter is corrupted by extraneous scatterers (similar to the disguise problem), and to investigate scenarios where scatterer occlusion takes place (similar to the face occlusion problem). Additional scenarios of whether the target azimuth position is completely or partially known are also examined.
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