SPARSITY-BASED RADAR IMAGING OF BUILDING STRUCTURES

In this paper, we address imaging of the interior structure of a building using a reduced number of measurements in through-the-wall imaging and urban sensing applica-tions. Unlike majority of the feature detection methods that are applied in the image domain, the proposed ap-proach works in the data domain and exploits prior infor-mation of construction practices together with the spar-sity described by the features. More specifically, the inte-rior walls are assumed to be either parallel or perpendic-ular to the front wall and a dictionary of possible wall lo-cations is proposed as a sparse representation of the scene. Compressive sensing is then applied to the reduced set of observations to recover the true positions of the walls. Supporting results based on laboratory experiments are provided. 1