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

Ping-Ping Ding (1) , Giacomo Oliveri (2) , Lorenzo Poli (2) , Andrea Massa (1, 2)

1 L2S - Laboratoire des signaux et systèmes
2 ELEDIA Research Group - Department of Information Engineering and Computer Science

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.

Keywords: Anisotropic layered media; 3-D scattering; Bayesian Compressive Sensing; sparsity; numerical experiments

Domains: Engineering Sciences [physics]; Electromagnetism; Mathematics [math]; Mathematical Physics [math-ph]; Statistics [stat]; Applications [stat.AP]

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⟩