Identifying defects in an unknown background using differential measurements

Lorenzo Audibert 1, 2 Girard Alexandre 2 Houssem Haddar 1
1 DeFI - Shape reconstruction and identification
CMAP - Centre de Mathématiques Appliquées - Ecole Polytechnique, Inria Saclay - Ile de France, X - École polytechnique, CNRS - Centre National de la Recherche Scientifique : UMR7641
Abstract : We present a new qualitative imaging method capable of selecting defects in complex and unknown background from differential measurements of farfield operators: i.e. far measurements of scattered waves in the cases with and without defects. Indeed, the main difficulty is that the background physical properties are unknown. Our approach is based on a new exact characterization of a scatterer domain in terms of the far field operator range and the link with solutions to so-called interior transmission problems. We present the theoretical foundations of the method and some validating numerical experiments in a two dimensional setting.
Type de document :
Article dans une revue
Inverse Probl. Imaging, AIMS, 2015, 9 (3), 〈10.3934/ipi.2015.9.625〉
Liste complète des métadonnées
Contributeur : Houssem Haddar <>
Soumis le : mardi 27 janvier 2015 - 17:52:47
Dernière modification le : jeudi 10 mai 2018 - 02:04:58

Lien texte intégral



Lorenzo Audibert, Girard Alexandre, Houssem Haddar. Identifying defects in an unknown background using differential measurements. Inverse Probl. Imaging, AIMS, 2015, 9 (3), 〈10.3934/ipi.2015.9.625〉. 〈hal-01110270〉



Consultations de la notice