Enhanced multilevel linear sampling methods for inverse scattering problems

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)554-571
Journal / PublicationJournal of Computational Physics
Volume257
Issue numberPA
Online published16 Oct 2013
Publication statusPublished - 15 Jan 2014
Externally publishedYes

Abstract

We develop two enhanced techniques for the multilevel linear sampling method (MLSM) proposed in [32] for inverse scattering problems. Under some practical situations, the MLSM suffers certain undesirable "breakage cells" problem. We propose to avoid the curse of "breakage cells" by incorporating "expanding" and "searching" techniques. The new techniques are shown to significantly improve the robustness of the MLSM, and meanwhile they possess the same optimal computational complexity as the MLSM. Numerical experiments are presented to illustrate the promising features of the enhanced MLSMs.

Research Area(s)

  • Enhanced multilevel linear sampling method, Inverse scattering problems, Optimal computational complexity

Citation Format(s)

Enhanced multilevel linear sampling methods for inverse scattering problems. / Li, Jingzhi; Liu, Hongyu; Wang, Qi.
In: Journal of Computational Physics, Vol. 257, No. PA, 15.01.2014, p. 554-571.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review