SVD-tail: A new linear-sampling reconstruction method for inverse scattering problems

M. Fares, Serge Gratton, Philippe Toint

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Abstract

A new efficient numerical procedure (SVD-tail) is proposed for the reconstruction of the shape and volume of unknown objects from measurements of their radiation in the far field. At variance with previously published linear-sampling methods where the solution is constructed as a regularized solution of the far-field equations using a variant of the Tikhonov-Morozov type, the new algorithm uses a new eigenspace recovery technique which exploits the combined presence of error in the operator and of eigenvalue clusters. Its performance on a battery of examples and its comparison with existing methods are shown to be promising. © 2009 IOP Publishing Ltd.
Original languageEnglish
Pages (from-to)1-19
Number of pages19
JournalInverse Problems
Volume25
Issue number9
DOIs
Publication statusPublished - 1 Jan 2009

Keywords

  • eigenspace recovery
  • linear sampling method
  • regularization heuristics
  • numerical algorithms.
  • inverse scattering

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