LAUSR

Ground-penetrating radar (GPR) technology plays an important role in near-surface geophysical surveys. Usually, the dataset acquired by a higher frequency antenna has higher resolution but limited penetration depth, while the dataset collected by a lower one has deeper penetration depth but lower resolution. It is necessary to fuse several different frequency datasets into a composite displayed profile to get a tradeoff between penetration depth and resolution. In such a case, we propose a novel multifrequency GPR data fusion method and test it on the data acquired from a limestone quarry in the Taihang Mountains of China. In our algorithm, time-varying weighting factors are calculated by the virtues of a sliding time window, i.e., designed with segmented signals. According to this approach, we can achieve better local characteristics of the signal and the smoothness of the signal waveform. The results show that the spectrum bandwidth of the fused signal is broadened, and the fusion profile significantly improves the imaging of internal structures for limestone on different scales.