Time-frequency joint imaging algorithm for borehole radar logging

In borehole radar logging identification technology, there are two key issues: target detection range and spatial resolution. Existing imaging algorithms face limitations in imaging distant targets, tracking moving targets, and identifying low-scattering cross-section features. To address the contradiction between detection range and resolution, we propose a novel time-frequency joint imaging algorithm based on direct-wave referenced processing. The algorithm implements three core strategies: (1) Amplitude normalization and time-base synchronization using the direct wave as a stable benchmark to suppress source jitter; (2) Hybrid-domain digital filtering combining wavelet transform and Fourier bandpass filtering to mitigate out-of-band noise; and (3) Adaptive time-varying amplification to compensate for spherical spreading and medium attenuation. Experimental results indicate that, compared to conventional high-resolution logging methods (e.g., acoustic/resistivity logging) limited to < 3 m, the proposed framework demonstrates a detection range extension to 8.5–10 m while simultaneously improving spatial resolution to the centimeter level (5–10 cm). This work presents a viable framework for long-range, high-resolution borehole radar imaging in complex formations, subject to further validation in diverse geological settings.