Enhancing GPR microwave imaging through innovative information acquisition techniques

Ground Penetrating Radar (GPR) is worldwide recognized as an efficient, other than effective, prospecting instrument for performing subsurface investigations [1],[2]. Its main applications involve both civil engineering and geophysical studies, as well as archaeology and military domains. Despite the remarkable plethora of available techniques developed by the scientific community in the last decades, many efforts are still needed to improve microwave imaging approaches applied to half-space scenarios. It is in fact well known that ill-posedness and non-linearity, characterizing free-space inverse problems [3], become even more relevant when dealing with subsurface configurations, given (i) the higher complexity of the scattering model, due to the presence of the (possibly rough) interface, and (ii) the limited amount of collectable information, mainly caused by the availability of strongly aspect-limited measurements. In order to partially mitigate the aforementioned problems several regularization techniques have been proposed, and the use of approximations aimed at linearizing the scattering equations has been widely considered for GPR imaging [1]. As a matter of fact, all these approaches are based on the availability of specific a-priori information on the unknown scenario at hand (such as, for example, the presence or not of weak scatterers), to effectively tackle the loss of information characterizing the inversion problem.