Solution strategies based on innovative evolutionary optimization techniques for microwave imaging applications

Microwave imaging (MI) is a technique aimed at obtaining information about a given configuration starting with measured samples of the scattered electric field. Usually, incident interrogating microwaves are used to sense the scene. Due to electromagnetic scattering laws, the problem to be faced is a highly ill-conditioned nonlinear inverse problem and, in general, the nonlinearity should be directly taken into account. Recently, most of the proposed approaches resort to optimization techniques. The paper considers the use of evolutionary algorithms for microwave imaging purposes. Innovative strategies are briefly illustrated, pointing out the relationship with previous works and the unique aspect of the current proposal. Moreover, these approaches are assessed (also in comparison with state-of-the-art methodologies) in order show their effectiveness in addressing specific inverse scattering problems which cannot be efficiently solved using standard "general purpose" techniques.