Time delay and permittivity estimation by ground penetrating radar with support vector regression
Résumé
In the field of civil engineering, sounding the pavement layers is classically performed using standard groundpenetrating radar (GPR), whose vertical resolution is bandwidth dependent. The layer thicknesses are deduced from both the time delays of backscattered echoes and the permittivity of layers. In contrast with conventional spectral analysis approaches, this paper focuses on one of the machine learning algorithms, namely, the Support Vector Machine (SVM), to perform Time Delay Estimation (TDE) and Dielectric Constant Estimation (DCE) of the medium from backscattered radar signals. This paper shows the super time resolution capability of such technique to resolve overlapping and fully correlated echoes within the context of thin pavement layers testing.