Assessing the structure of a building with non-invasive methods is an important problem. One of the possible approaches is to use GeoRadar to examine wall structures by analyzing the data obtained from the scans. We propose a data-driven approach to evaluate the material composition of a wall from its GPR radargrams. In order to generate training data, we use gprMax to model the scanning process. Using simulation data, we use a convolutional neural network to predict the thicknesses and dielectric properties of walls per layer. We evaluate the generalization abilities of the trained model on data collected from real buildings.
@article{arxiv.2208.12064,
title = {Assesment of material layers in building walls using GeoRadar},
author = {Ildar Gilmutdinov and Ingrid Schloegel and Alois Hinterleitner and Peter Wonka and Michael Wimmer},
journal= {arXiv preprint arXiv:2208.12064},
year = {2022}
}