Wavefront Reconstruction and Diffraction-Driven GPR Inversion by Semblance-Based Coherence Analysis

The essentiality of diffraction wavefront in structural mapping has been perceived, mainly because of its imaging potential for small structural variations and microscopic discontinuities. However, full extraction of ground penetrating radar (GPR) diffractions cannot be done perfectly even in theory as the faint components are typically masked by the more dominant reflections, resulting in a resolution loss of minutiae features. To address these issues, this letter develops a semblance-based coherence analysis framework for GPR diffraction wavefront reconstruction and full waveform inversion (FWI). Specifically, adaptive amplitude restoration is initially performed using the mean instant amplitude for analytic attenuation function derivation, which is followed by modified multitrace coherence stacking. Diffraction reconstruction is then executed with corrective factors determined by EM semblance attributes, while being assessed by quantified indices for reconstruction performance. The proposed framework is tested for validity and practicality with a synthetic model and laboratory experiment by comparing the conventional FWI and the diffraction driven FWI. The results present a high-resolution image of diffraction occurrences even with a homogeneous initial model, and more intuitively show a higher-resolution image even with a suboptimal initial model by diffraction-driven permittivity analysis. These encouraging results could potentially enable a hybrid inversion which benefits from reconstructing both GPR reflections and diffractions.