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EFFICIENT SPARSE ALGORITHM FOR SOLVING MULTI-OBJECTS SCATTERING BASED ON COMPRESSIVE SENSING

By D. Chai and Y. Wang

Full Article PDF (413 KB)

Abstract:
To improve computational efficiency of traditional method for solving separable multi-objects scattering problems, each subdomain impedance matrix is sparsified by biorthogonal lifting wavelet transform (BLWT) without allocating auxiliary memory, and a sparse underdetermined equation is constructed by enjoying the prior knowledge from known excitation in wavelet domain, then orthogonal matching pursuit (OMP) is employed to fast and accurately solve the sparse underdetermined equation under compressive sensing (CS) framework. Numerical results of separable perfectly electric conduct (PEC) multi-objects are presented to show the efficiency of the proposed method.

Citation:
D. Chai and Y. Wang, "Efficient Sparse Algorithm for Solving Multi-Objects Scattering Based on Compressive Sensing," Progress In Electromagnetics Research M, Vol. 84, 43-51, 2019.
doi:10.2528/PIERM19051205

References:


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