Wavelet dispersion caused by frequency-dependent attenuation is a common occurrence in ground-penetrating radar (GPR) data, and is displayed in the radar image as a characteristic blurriness that increases with depth. Correcting for wavelet dispersion is an important step that should be performed before GPR data are used for either qualitative interpretation or the quantitative determination of subsurface electrical properties. Over the bandwidth of a GPR wavelet, the attenuation of electromagnetic waves in many geological materials is approximately linear with frequency. As a result, the change in shape of a radar pulse as it propagates through these materials can be well described using one parameter, Q*, related to the slope of the linear region. Assuming that all subsurface materials can be characterized by some Q* value, the problem of estimating and correcting for wavelet dispersion becomes one of determining Q* in the subsurface and deconvolving its effects using an inverse-Q filter. We present a method for the estimation of subsurface Q* from reflection GPR data based on a technique developed for seismic attenuation tomography. Essentially, Q* is computed from the downshift in the dominant frequency of the GPR signal with time. Once Q* has been obtained, we propose a damped-least-squares inverse-Q filtering scheme based on a causal, linear model for constant-Q wave propagation as a means of removing wavelet dispersion. Tests on synthetic and field data indicate that these steps can be very effective at enhancing the resolution of the GPR image.
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