Reconstruction of 3D Objects in Anisotropic Multi-layered Media by a Bayesian Compressive Sensing Solver

Abstract : This paper investigates an innovative imaging approach for reconstructing 3D objects in complex anisotropic multi-layered media. A fast algorithm applied for solving the electromagnetic scattering problems in the anisotropic multi-layered media is integrated with a Bayesian Compressive Sensing solver for the reconstruction of sparse scatterers. The validity of the novel imaging approach and its effectiveness and robustness are validated through numerical experiments.
Type de document :
Communication dans un congrès
F. Kojima. The 17th International Symposium on Applied Electromagnetics and Mechanics (ISEM 2015), Sep 2015, Awaji City - Hyogo, Japan. Proceedings ISEM 2015, pp.2P1-C-4, 2015, 〈http://www.org.kobe-u.ac.jp/isem2015/home.html〉
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https://hal-centralesupelec.archives-ouvertes.fr/hal-01250002
Contributeur : Dominique Lesselier <>
Soumis le : lundi 4 janvier 2016 - 11:19:17
Dernière modification le : jeudi 11 janvier 2018 - 06:19:10

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  • HAL Id : hal-01250002, version 1

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Ping-Ping Ding, Giacomo Oliveri, Lorenzo Poli, Andrea Massa. Reconstruction of 3D Objects in Anisotropic Multi-layered Media by a Bayesian Compressive Sensing Solver . F. Kojima. The 17th International Symposium on Applied Electromagnetics and Mechanics (ISEM 2015), Sep 2015, Awaji City - Hyogo, Japan. Proceedings ISEM 2015, pp.2P1-C-4, 2015, 〈http://www.org.kobe-u.ac.jp/isem2015/home.html〉. 〈hal-01250002〉

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