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Experimental Demonstration of Bistatic Radar Tomography using Parameter-Refined OMP

This paper considers the problem of bistatic radar tomographic imaging within the framework of sparse reconstruction and compressive sensing. The bistatic radar tomography problem is first reformulated as a sparse inverse problem and the Parameter-Refined Orthogonal Matching Pursuit algorithm is then derived to obtain a sparse solution. Numerical results obtained for experimental data are presented to demonstrate the efficacy of the method.