Diffraction Separation by a Coherence Analysis Framework for Ground Penetrating Radar Applications

Diffraction separation is considered of great importance for the full-wavefront reconstruction (FWR) of ground penetrating radar (GPR) and its delicate data processing. In contrast to reflections, GPR diffraction events encode the fully dynamic feature and subwavelength information to identify small-scale heterogeneities, thereby offering enhanced illumination and resolution for GPR imaging. However, fully extracting these faint diffraction components remains a very challenging task. These components are usually ignored because of the strong interference and masking effect of the more dominant reflective components, and in particular, the attenuation of GPR waves accelerates almost exponentially with the frequency. In this article, we developed a coherence analysis (CA) framework for extracting GPR diffractions by considering the kinematic attributes and discontinuity features of GPR wavefronts, as well as the dispersion and attenuation effects of GPR responses. To be specific, the compensation preprocessing and semblance summation are performed sequentially for coherence acquisition, after which a multiscale subtraction is designed toward the coherent fields. In particular, we concentrated on analyzing media losses and multiparameter impacts on diffraction separation performance. To demonstrate the feasibility and practicality of the proposed framework, we tested our algorithm using synthetic and field datasets, both results with quantified metrics showing the elimination of continuities. The comparative results reveal the performance of the framework in preserving the edge components of GPR diffractions, making it potentially attractive for microscopic velocity analysis, refined full wavefield migration (FWM), and well-constrained full waveform inversion in terms of small-scale heterogeneities and discontinuities.