Sparse Reconstruction Algorithms for Nonlinear Microwave Imaging

Hidayet Zaimaga (1) , Aurélia Fraysse (1) , Marc Lambert (2)

1 L2S - Laboratoire des signaux et systèmes
2 GeePs - Laboratoire Génie électrique et électronique de Paris

This paper presents a two-step inverse process which allows sparse recovery of the unknown (complex) dielectric profiles of scatterers for nonlinear microwave imaging. The proposed approach is applied to a nonlinear inverse scattering problem arising in microwave imaging and correlated with joint sparsity which gives multiple sparse solutions that share a common nonzero support. Numerical results demonstrate the potential of the proposed two step inversion approach when compared to existing sparse recovery algorithm for the case of small scatterers.

Keywords: unknown dielectric profiles; step inversion approach; sparse reconstruction algorithms; multiple sparse solutions; nonlinear inverse scattering problem; nonlinear microwave imaging; sparse recovery algorithm

Domains: Engineering Sciences [physics]; Electromagnetism

Hidayet Zaimaga, Aurélia Fraysse, Marc Lambert. Sparse Reconstruction Algorithms for Nonlinear Microwave Imaging. 25th European Signal Processing Conference (EUSIPCO 2017), Aug 2017, Kos island, Greece. pp.743-747, ⟨10.23919/eusipco.2017.8081300⟩. ⟨hal-01587676⟩