Rayleigh Wave Reconstruction from Ambient Noise Cross-Correlation Function by Radon-Wigner Transform

Abstract

The ambient noise tomography is a powerful underground-structure-detection method developed in recent years. The key of this technique is to extract Rayleigh-wave signals from cross-correlation functions (CCF). It is important to suppress the noise in Rayleigh wave signals to increase the accuracy of dispersion-curve extraction. In this paper, a Radon-Wigner Transform (RWT) method is used for Rayleigh-wave reconstruction from CCF. We first introduce the principles of RTW, and then use a multi-component synthetic seismic data to show the processing steps of RWT. Finally, we process actual ambient noise CCF with RWT to reconstruct Rayleigh waves. The results of the synthetic and actual data examples indicate that RWT successfully reconstructed the Rayleigh waves from CCF and improved the signal-to-ratio of the signal.