Electromagnetic Imaging of Closely Spaced Objects Using Matching Pursuit Based Approaches


During this letter, sparse signal recovery framework is applied for the reconstruction of 2 closely placed point-like objects from measured scattered electromagnetic field. Greedy matching pursuit-primarily based algorithms are investigated as the sparsity promoting technique. The performances of the matching pursuit algorithms are compared against convex relaxation methods. Orthogonal matching pursuit algorithm implemented with a flexible tree structure is shown to improve the resolution for the inverse scattering downside.

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