Hilbert-Huang transformation and noise suppression of magnetotelluric sounding data
Hilbert-Huang 变换与大地电磁噪声压制

Magnetotelluric signals are nonlinear, non-stationary, non-minimum phase, they do not meet the basic requirements of the Fourier transform based on the traditional power spectrum estimation. Hilbert-Huang Transformation is an entirely local time-frequency analysis method developed in recent years for dealing with non-linear, non-stationary signals. This paper briefly introduced the Hilbert-Huang Transform basic principles and algorithms. Based on the analysis of actual data examples, we discussed its application in magnetotelluric signal processing and noise suppression. It has been founded that selecting magnetotelluric signal sessions using Hilbert time-frequency energy spectrum is helpful to improve signal quality and enhance the quality of data processing and information interpretability. Using empirical mode decomposition method and multi-scale filter characteristics can effectively analyze the noise distribution of MT signal and suppress interference.