Quantitative Analysis of GPR Signals: Transmitted Wavelet, Amplitude Decay, and Sampling-Related Amplitude Distortions

We study the importance of accurately recording signal amplitudes for the quantitative analysis of GPR data sets. Specifically, we measure the peak amplitudes of signals emitted by GPR antennas with different central frequencies and study their amplitude decay with distance, in order to extrapolate the peak amplitude of the wavelet initially transmitted by each antenna. The purpose is to compare the reference and reflected amplitudes in order to accurately estimate the subsurface EM impedance contrasts. Moreover, we study how sampling-related amplitude distortions can affect the quantitative analysis, and subsequently the resulting subsurface models, even in the absence of aliasing effects. The well-known Nyquist\u2013Shannon theorem gives practical lower limits for the sampling rate in order to preserve the spectral content of a digitized signal; however, we show that it does not prevent possible amplitude distortions. In particular, we demonstrate that significant and unrecoverable loss of amplitude information occurs even at sampling rates well above the Nyquist\u2013 Shannon threshold. Interpolation may theoretically reduce such amplitude distortions; however, its accuracy would depend on the implemented algorithm and it is not verifiable in real data sets, since the actual amplitude information is limited to the sampled values. Moreover, re-sampling the interpolated signal simply reintroduces the initial problem, when a new sampling rate is selected. Our analysis suggests that, in order to limit the maximum peak amplitude error within 5%, the sampling rate selected during data acquisition must be at least 12 times the signal central frequency, which is higher than the commonly adopted standards