Processing GPR data with 2D Bayesian compressive sensing inverse scattering approaches

In this work, the solution of the subsurface microwave imaging problem is addressed through innovative inverse scattering (IS) approaches. Towards this end, wide-band ground penetrating radar (GPR) measurements are processed by means of Bayesian Compressive Sensing (BCS)-based strategies integrated with frequency-hopping (FH) or multi-frequency (MF) inversion schemes. Thanks to the additional information provided by the frequency diversity of GPR data and the formulation of suitable sparseness-regularized methodologies faithful reconstructions are yielded under several operative conditions, as clearly indicated by selected numerical experiments.