Empirical Mode Decomposition Operator for Dewowing GPR Data

Abstract

Signal processing tools available to ground penetrating radar data used for shallow subsurface imaging and hydrogeophysical parameter estimation are significantly handled using the same tools available to seismic reflection data. Overall, the same tools produce interpretable images from both data types, but particular noise (wow noise) in electromagnetic data must be removed before stable and accurate quantitative results can be produced. Wow noise is an inherent, nonlinear electromagnetic interference and a significant component of GPR data. Further, the nonlinear and non-stationary nature of wow noise provides a strong argument for preprocessing radar traces with time-domain operators. Time-domain operators designed for nonlinear signals are under increasing development for both electromagnetic and acoustic signal processing. This work demonstrates optimal wow noise removal from ground penetrating radar data using the empirical mode decomposition. The technique provides a data-driven approach to empirically dewowing GPR data.