Wavelet analysis for ground penetrating radar applications: a case study

Abstract

Noises may significantly disturb ground penetrating radar (GPR) signals, therefore, filtering undesired information using wavelet analysis would be challenging, despite the fact that several methods have been presented. Noises are gathered by probe, particularly from deep locations, and they may conceal reflections, suffering from small altitudes, because of signal attenuation. Multiple engineering fields need data analysis to distinguish valued material, based on information obtained by underground observations. Using wavelets as one of the useful methods for analyzing data is considered in this paper. However, optimal wavelet analysis would be challenging in the realm of exploring GPR signals. There is no doubt that accounting for wavelet function, decomposition level, threshold estimation method and threshold transformation, in the matter of de-noising and investigating signals, is of great importance; they must be chosen with judgment as they influence the results enormously if they are not carefully designated. Multiple wavelet functions are applied to perform de-noising and reconstruction on synthetic noisy signals generated by the finite-difference time-domain (FDTD) method to account for the most appropriate function for the purpose. In addition, various possible decomposition levels, threshold estimation methods and threshold transformations in the de-noising procedure are tested. The optimal wavelet analysis is also evaluated by examining real data acquired from several antenna frequencies which are common in engineering practice.