3D Markov Random Field in realistic inverse scattering

This communication deals with the reconstruction of three-dimensional target from experimental multiple-frequency data measured in the anechoic chamber of the Institut Fresnel (Marseille, France). In order to take into account the random noise present in the experiments, a Bayesian approach is considered. In particular, the inversion procedure takes advantage from the joint use of the Contrast Source-Extended Born model and of a Markov Random Field regularization. We also considered a cost functional appropriately weighted by coefficients which change with the frequency, the incident angle and the receiving angle. In fact, each scattered field measurement is balanced with the noise disturbing the data.