| Ground Penetrating Radar, GPR, is a widely used tool for probing the sub-surface in such applications as pavement monitoring, humanitarian de-mining, and exploratory geophysics, among others. Its advantage lies in that it provides information about the composition of the sub-surface in a fast, non-invasive fashion.; The work presented herein relies on the application of GPR to the problems of material type, e.g., soil types, and soil moisture determination. The task is attacked from a systems perspective to obtain a signature for each material at different moisture levels. This signature has discriminatory characteristics that are exploited with the use of a Neural Network, NN, which is able to distinguish between different materials and moisture levels with reasonable accuracy. |
