A Method of Reconstructing Ground Penetrating Radar Bscan for Advanced Detection Based on High-Order Synchrosqueezing Transform

Accurately predicting geological structures (GSs) ahead of tunnel excavation is of paramount importance for ensuring safety in coal mines. The standard time or frequency analysis methods face significant challenges due to limitations in downhole environments and ground penetrating radar (GPR) instrument performance, hindering the acquisition of precise geological information. Time–frequency (TF) analysis, capable of simultaneously examining nonstationary signals in both time and frequency domains, has become an important tool for interpreting GPR data. High-order synchrosqueezing transform (HSST) has a solid mathematical foundation and higher TF resolution than linear TF transforms and synchrosqueezing transforms (SSTs). In this study, we propose a method utilizing HSST to extract TF features of GS responses and reconstruct them into novel Bscan for advanced detection of GSs. Experimental examples using GPR forward simulation data containing GSs demonstrate the method’s precise characterization and intuitive visualization capabilities for GS interfaces, even in noise-polluted environments. Additionally, we present a real GPR data example that demonstrates the method’s ability to intuitively and accurately characterize the front GS interface. Field revelations provide robust verification of the method’s accuracy and practical applicability.