A de-noising method of magnetotelluric signals based on the generalized S-transform

Abstract

The generalized S-transform has excellent time-frequency resolution capability. It can effectively demonstrate the non-stationary characteristics of signals and the dynamic changes in energy. This provides the conditions for denoising in the time-frequency domain. The magnetotelluric (MT) survey method is often affected by various artificial noises, and these noises are very prominent in certain frequency bands. To address this problem, a method based on the generalized S transform is proposed to de-noise MT data. The generalized S transform is used to improve the time-frequency localization of the different signal components, meanwhile the electromagnetic noise can be conveniently suppressed in the time-frequency domain. Simulated signals and measured MT signals contaminated by common sinusoidal and triangular wave interference are processed. The results were compared with those of the Wavelet threshold method. Results show that the presented method is more conducive to the identification and suppression of electromagnetic noise and shows better de-noising results than the Wavelet threshold method. After de-noising, the useful information of the MT signal affected by strong interference is highlighted, which provides favorable conditions for power spectrum and impedance estimation in the future. Further, the response parameter curve calculated from the de-noised data becomes stable. The proposed method provides a new alternative for de-noising of MT signals, especially those with low signal-to-noise ratios.