Three-dimensional sparse electromagnetic imaging accelerated by projected steepest descent

Abdulla Desmal, Hakan Bagci

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

An efficient and accurate scheme for solving the nonlinear electromagnetic inverse scattering problem on three-dimensional sparse investigation domains is proposed. The minimization problem is constructed in such a way that the data misfit between measurements and scattered fields (which are expressed as a nonlinear function of the contrast) is constrained by the contrast's first norm. The resulting minimization problem is solved using nonlinear Landweber iterations accelerated using a steepest descent algorithm. A projection operator is applied at every iteration to enforce the sparsity constraint by thresholding the result of that iteration. Steepest descent algorithm ensures accelerated and convergent solution by utilizing larger iteration steps selected based on a necessary B-condition.
Original languageEnglish (US)
Title of host publication2016 IEEE International Symposium on Antennas and Propagation (APSURSI)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1029-1030
Number of pages2
ISBN (Print)9781509028863
DOIs
StatePublished - Nov 2 2016

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