A Novel Transform For Extracting Dispersion Curve From Multiple Components of Ambient Noise Cross-correlation Function

Ambient noise tomography has been a widely used method for imaging the structure of the lithosphere. A key step in this method is extracting the dispersion curve from ambient noise cross-correlation. Based on the single force displacement formula of Generalized Reflection and Transmission method, we obtained the type of Bessel function in different components of the cross-correlation function. Borrowing the idea of the S transformation and replacing the exponential function in which with the corresponding Bessel function to different components of cross-correlation function, we define a new transformation, named SJ transformation, to extract Rayleigh wave dispersion curve from ZZ, ZR, RZ, RR component and Love wave dispersion curve from TT component. Using synthetic test, the extracted dispersion curve fits the theoretical dispersion curve well, which’s error rate < 1%, and in field data test, the extracted dispersion curve of the Rayleigh wave from different component matches each other well. Although the SJ spectrum of ZZ component may be distorted by noise, there may be no influence in other components, which provide the possibility to extract Rayleigh wave dispersion curve with a wider frequency band.