Three-dimensional sparse electromagnetic imaging accelerated by projected steepest descent
Type
Conference PaperAuthors
Desmal, Abdulla
Bagci, Hakan

KAUST Department
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) DivisionElectrical Engineering Program
Date
2016-11-02Online Publication Date
2016-11-02Print Publication Date
2016-06Permanent link to this record
http://hdl.handle.net/10754/622487
Metadata
Show full item recordAbstract
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.Citation
Desmal 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 name
2016 IEEE Antennas and Propagation Society International Symposium, APSURSI 2016Additional Links
http://ieeexplore.ieee.org/document/7696222/ae974a485f413a2113503eed53cd6c53
10.1109/APS.2016.7696222