Diffractions caused by, e.g., faults, fractures, and small-scale heterogeneity localized near the surface are often used in ground-penetrating radar (GPR) reflection studies to constrain the subsurface velocity distribution using simple hyperbola fitting. Interference with reflected energy makes the identification of diffractions difficult. We have tailored and applied a diffraction imaging method to improve imaging for surface reflection GPR data. Based on a plane-wave destruction algorithm, the method can separate reflections from diffractions. Thereby, a better identification of diffractions facilitates an improved determination of GPR wave velocities and an optimized migration result. We determined the potential of this approach using synthetic and field data, and, for the field study, we also compare the estimated velocity structure with crosshole GPR results. For the field data example, we find that the velocity structure estimated using the diffraction-based process correlates well with results from crosshole GPR velocity estimation. Such improved velocity estimation may have important implications for using surface reflection GPR to map, e.g., porosity for fully saturated media or soil moisture changes in partially saturated media because these physical properties depend on the dielectric permittivity and thereby also the GPR wave velocity.
Compressive Sensing Based Three-Dimensional Imaging Method with Electro-Optic Modulation for Nonscanning Laser Radar
