Abstract
Stochastic and deterministic deconvolution methods encounter difficulties in increasing the temporal resolution of GPR data. Statistical approaches, such as predictive or spiking deconvolution are not effective when the wavelet is non-minimum phase, which is the case for GPR data. Wavelet deconvolution is not successful due to the non-stationarity of the GPR trace. Here, prior deconvolution, we apply a spectral balancing method in t-f domain which efficiently reduces the non-stationarity. The proposed methodology invovlves correction for phase residuals using the maximum kurtosis method. The effectiveness of this methodology is demonstrated on synthetic and real GPR data.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have