Application of time-reversal-based processing techniques to enhance detection of GPR targets

TL;DR

This paper evaluates time-reversal techniques combined with various pre-processing methods to improve the detection and localization of subsurface targets using Ground Penetrating Radar data.

Contribution

It introduces a novel application of time-reversal processing to GPR data, demonstrating enhanced target detection and differentiation capabilities.

Findings

Time-reversal techniques improve target localization accuracy.

Pre-processing methods enhance signal clarity and target distinguishability.

Method shows potential for practical GPR target detection applications.

Abstract

In this paper we analyze the performance of time-reversal (TR) techniques in conjunction with various Ground Penetrating Radar (GPR) pre-processing methods aimed at improving detection of subsurface targets. TR techniques were first developed for ultrasound applications and, by exploiting the invariance of the wave equation under time reversal, can yield features such as superresolution and statistical stability. The TR method was examined here using both synthetic and actual GPR field data under four different pre-processing strategies on the raw data, namely: mean background removal, eigenvalue background removal, a sliding-window space-frequency technique, and a noise-robust spatial differentiator along the scan direction. Depending on the acquisition mode, it was possible to determine with good precision the position and depth of the studied targets as well as, in some cases, to differentiate the targets from nearby clutter such as localized geological anomalies. The proposed methodology has the potential to be useful when applied to GPR data for the detection of buried targets.