An unsupervised strategy based on a fuzzy-logic system for the exploitation of the information content of noisy data in inverse scattering problems

Inverse scattering data, although collected in a controlled environment, are generally corrupted by an electromagnetic noise, which strongly affects the effectiveness of reconstruction strategies because of the intrinsic ill-conditioning of the problem. To limit the effects of the noise on the retrieval procedure, this paper presents an innovative fuzzy-logic-based approach, which allows one to take into account the corrupted nature of the data by fully exploiting all the available information content of the measurements. Selected numerical experiments in a noisy scenario are considered for assessing the potentialities of the approach also in comparison with a reference inverse scattering technique.