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Partially Sparse Imaging of Stationary Indoor Scenes

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Journal Article - Open Access

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Villanova University Villanova United States

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In this paper, we exploit the notion of partial sparsity for scene reconstruction associated with through-the-wall radarimaging of stationary targets under reduced data volume. Partial sparsity implies that the scene being imaged consistsof a sparse part and a dense part, with the support of the latter assumed to be known. For the problem at hand,sparsity is represented by a few stationary indoor targets, whereas the high scene density is defined by exterior andinterior walls. Prior knowledge of wall positions and extent may be available either through building blueprints orfrom prior surveillance operations. The contributions of the exterior and interior walls are removed from the datathrough the use of projection matrices, which are determined from wall- and corner-specific dictionaries. Theprojected data, with enhanced sparsity, is then processed using 1 norm reconstruction techniques. Numericalelectromagnetic data is used to demonstrate the effectiveness of the proposed approach for imaging stationary indoorscenes using a reduced set of measurements.

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  • Active and Passive Radar Detection and Equipment

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