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.

Use of Ground Penetrating Radar to Study Spatial Variability and Soil Stratigraphy

“…For each trace, it calculated the mean of the points on either side of that point within a specified time range. Then, the mean was subtracted from the original point (Bradley et al, 2009). The gain function step helped to visualize data late in the time series of each trace.…”

Signal Processing of GPR Data for Road Surveys

“…Nevertheless, attention must be paid to avoid potential distortion effects on the signal and, hence, loss of information [57]. According to the literature, time-varying high-pass filtering or the Empirical Decomposition Method (EMD) [58] are regarded as alternative processing methods to de-wow. Figure 6 shows the reference GPR radargram after applying a de-wow filter.…”

“…Noise due to the surrounding media and the inherent loss of the GPR signal usually lowers the SNR in a GPR section, especially at relatively late recording times [58,64]. These noise components are generally located outside the main working frequency bandwidth of a GPR system.…”

“…If applicable, the most correct approach is to apply time-varying band-pass filtering. For example, EMD [58] or a user-defined time varying band-pass filtering in the t-f domain [64] could be used.…”

Optimal filtering high-resolution seismic reflection data using a weighted-mode empirical mode decomposition operator

“…Despite a quite large use of this technique in several fields of digital signal processing (Pai et al, 2007;Schmitt et al, 2007;Sweeney-Reed and Nasuto, 2007) only a few examples have been shown in geophysical data processing Battista et al, 2007Battista et al, , 2009Magrin-chagnolleau and Baraniuk, 1999).…”