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.
Radar target recognition using structured sparse representation