Ground penetrating radar (GPR) technology for underground exploration consists in the transmission of an electromagnetic signal in the ground for sensing the presence of buried objects. While monostatic or bistatic configurations are usually adopted, a limited number of multistatic GPR systems have been proposed in the scientific literature. In this manuscript, we investigate the recovery performance of a specific and unconventional contactless multistatic GPR system, designed at the Georgia Institute of Technology for the subsurface imaging of anti-tank and anti-personnel plastic mines. In particular, for the first time, tomographic approaches are tested against this experimental multistatic GPR system, while most GPR processing in the scientific literature processes multi-monostatic experimental data sets. Firstly, by mimicking the system at hand, an accurate theoretical as well as numerical analysis is performed in order to estimate the data information content and the performance achievable. Two different tomographic linear approaches are adopted, i.e. the linear sampling method (LSM) and the Born approximation (BA) method, this latter enhanced by means of the compressive sensing (CS) theoretical framework. Then, the experimental data provided by the Georgia Institute of Technology are processed by means of a multi-frequency CS and BA-based method, thus generating very accurate 3D maps of the investigated underground scenario. Index Terms-ground penetrating radar (GPR), inverse scattering (IS) problem, microwave tomography, plastic landmine detection, linear sampling method (LSM), Born approximation (BA), compressive sensing (CS), sparse recovery.
I. INTRODUCTIONROUND-PENETRATING radar (GPR) represents a powerful technology able to investigate in a non-invasive and non-destructive way non-accessible scenarios, as witnessed by the numerous and different applications, which include demining, lunar explorations, archaeology, geology, and civil engineering [1].GPR technology is usually adopted for subsurface imaging