Reconstruction of piecewise constant objects in microwave imaging in a 2D-TE configuration

In this paper we propose a stochastic algorithm applied to an electromagnetic inverse scattering problem. The objective is to characterize an unknown object from measurements of the scattered fields at different frequencies and for several illuminations. This inverse problem is known to be nonlinear and ill-posed. It then needs to be regularized by introducing prior information. The particular prior information we account for is that the object is composed of a finite known number of different materials distributed in compact regions. The algorithm is applied to the inversion of experimental data collected at the Institut Fresnel (Marseille) and has already provided satisfactory results in a 2D-TM configuration. Herein, the goal is to test the same kind of method in a 2D-TE configuration.