Three-dimensional sparse electromagnetic imaging accelerated by projected steepest descent
KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program
Online Publication Date2016-11-02
Print Publication Date2016-06
Permanent link to this recordhttp://hdl.handle.net/10754/622487
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AbstractAn 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.
CitationDesmal A, Bagci H (2016) Three-dimensional sparse electromagnetic imaging accelerated by projected steepest descent. 2016 IEEE International Symposium on Antennas and Propagation (APSURSI). Available: http://dx.doi.org/10.1109/APS.2016.7696222.
Conference/Event name2016 IEEE Antennas and Propagation Society International Symposium, APSURSI 2016