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.
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https://hal-centralesupelec.archives-ouvertes.fr/hal-01250002
Contributor : Dominique Lesselier <>
Submitted on : Monday, January 4, 2016 - 11:19:17 AM
Last modification on : Thursday, April 5, 2018 - 12:30:05 PM

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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 . The 17th International Symposium on Applied Electromagnetics and Mechanics (ISEM 2015), Sep 2015, Awaji City - Hyogo, Japan. pp.2P1-C-4. ⟨hal-01250002⟩

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