Postprocessing of the linear sampling method in inverse electromagnetic scattering problem for obstacles

Lei Liu, Weinong Fu, Shuangxia Niu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

The linear sampling method is known to be a simple and computationally efficient approach to retrieve the support of the scatterer using multistatic scattered field data. However, the recovered profile is always misleading, owing to the lack of robust edge detecting. This paper addresses this open issue. Using moving least square approximation, the upper and lower bounds of the profile of scatterers are pursued, and a sweeping process finds the optimal profile to match the scattered field data.
Original languageEnglish
Title of host publicationIEEE CEFC 2016 - 17th Biennial Conference on Electromagnetic Field Computation
PublisherIEEE
ISBN (Electronic)9781509010325
DOIs
Publication statusPublished - 12 Jan 2017
Event17th Biennial IEEE Conference on Electromagnetic Field Computation, IEEE CEFC 2016 - Hotel Hilton Miami Downtown, Miami, United States
Duration: 13 Nov 201616 Nov 2016

Conference

Conference17th Biennial IEEE Conference on Electromagnetic Field Computation, IEEE CEFC 2016
Country/TerritoryUnited States
CityMiami
Period13/11/1616/11/16

Keywords

  • Curvature
  • Inverse scattering
  • Linear sampling method
  • Moving least square method

ASJC Scopus subject areas

  • Computational Mathematics
  • Instrumentation
  • Electrical and Electronic Engineering

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