Applications of Ground-Penetrating Radar (GPR) to Detect Hidden Beam Positions

Abstract

Ground-penetrating radar (GPR) uses electromagnetic waves to investigate the structures. In this investigation method, an electromagnetic wave is transmitted using an antenna and the received signal is recorded. Detection of beam positions in this GPR data requires the skills of a trained human operator. This study utilized a multi-layer neural network to detect beam positions in the GPR data. The visual description and definition of GPR data has major disadvantages and a neural network has been studied to overcome these shortcomings. A set of 32,740 training vectors with a length of 64 data was implemented to train the neural network. A new set of 16,370 testing vectors with a length of 64 data was then prepared to test the performance. Testing results suggest that the neural network is promising methods for the detection of beam positions in the GPR data.