Subsurface sensing and non-destructive evaluation with Ground Penetrating Radar (GPR)

Ground Penetrating Radar (GPR) is a non-destructive imaging system that is widely adopted in subsurface prospection (e.g., for soil mapping, demining, utility detection, ...) and civil structure monitoring (e.g., defect and rebar characterization in concrete structures, road pavement monitoring, tree roots inspection, ...). The output of GPR systems is usually provided as a B-scan (a two-dimensional plot of the amplitude of the received electromagnetic pulse versus time). Such a representation is however difficult to interpret and requires skilled users.

A significant enhancement can be obtained by using inverse scattering techniques for processing the measured data, since they are able to directly provide an image of the dielectric properties of the inspected region. However, it is required to solve a nonlinear and ill-posed inverse scattering problem, where a set of parameters describing the underground scenario must be retrieved starting from samples of the measured electromagnetic field. The imaging problem is further complicated by the fact that often only limited-view data are usually available.

The present Thesis topic aims at developing and validating ad-hoc novel techniques for GPR data processing. The activity may also benefit with the cooperation with other national and international groups.

For further details and any other information, please contact Profs. Matteo Pastorino (, Andrea Randazzo ( and/or Alessandro Fedeli (



Some cooperations:

  • Sapienza University of Rome, Italy
  • University of Trento, Italy
  • Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR), France
  • Université Catholique de Louvain, Belgium

Selected recent publications:

  • C. Estatico, A. Fedeli, M. Pastorino, and A. Randazzo, ‘‘Variable-exponent Lebesgue-space inversion for cross-borehole subsurface imaging’’, URSI Radio Science Letters, vol. 1, pp. 1-5, 2020.
  • C. Estatico, A. Fedeli, M. Pastorino, and A. Randazzo, “Buried Object Detection by Means of a Lp Banach-Space Inversion Procedure,” Radio Science, vol. 50, no. 1, pp. 41-51, Jan. 2015.


Thesis type