Time Delay and Permittivity Estimation by Ground-Penetrating Radar With Support Vector Regression

摘要

In the field of civil engineering, sounding the pavement layers is classically performed using standard ground-penetrating radar, 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 letter focuses on one of the machine learning algorithms, namely, the support vector machine, to perform time delay estimation and dielectric constant estimation of the medium from backscattered radar signals. This letter shows the super time resolution capability of such technique to resolve overlapping and fully correlated echoes within the context of thin pavement layer testing.