Research on ground-penetrating radar denoising algorithm based on CEEMD and Permutation Entropy

When ground-penetrating radar detects complex and diverse geological structures in the subsurface, the returned detection signals are easily affected by various types of environ-mental noise, which brings serious interference to the interpre-tation targets. This paper proposes a ground-penetrating radar data processing method based on the combination of empirical modal decomposition of complementary sets and permutation entropy, which can decompose the ground-penetrating radar data into several IMF components and determine the separation threshold between the target signal and the noise signal through the calculation of the permutation entropy of these components, so as to achieve the effect of noise removal, and the effectiveness of the method is demonstrated through relevant experiments.