New tomographic imaging strategies for GPR surveys

Tomographic methods nowadays represent an assessed means to process GPR data, as they allow to obtain images that are more reliable and readable than those achieved using standard GPR data processing tools. However, tomographic approaches are based on a suitable modeling of the electromagnetic scattering phenomenon, which is required to cast the underlying inverse problem. In particular, the non-linearity of the inverse problem entails that solution methods are extremely sensitive to modeling errors and, even worse, are prone to the occurrence of false solutions, that is, estimates of the unknown function that match the data but are different from the ground truth. As such, most of the effective applications of tomographic GPR are so far concerned with linearized inversion approaches, which are based on simple models and are indeed free from false solutions. However, they can only provide information on the location of buried targets and not on their electromagnetic features. In this paper, we present a new tomographic approach that, being based on a “scenario specific” linearized model arising from a suitable preprocessing of the measured data, allows to both achieve information on the electromagnetic features and avoid occurrence of false solutions. The method is presented and numerically assessed for the case of cross-borehole GPR surveys.