Random Noise Suppression of Magnetic Resonance Sounding Oscillating Signal Based on Cross Correlation

Abstract

Magnetic resonance sounding (MRS) is a noninvasive geophysical method, which may detect the underground water directly. However, the weak MRS signals oscillating at Larmor frequency always suffer from low signal-to-noise ratios (SNRs) due to the multisource noise, especially the random noise. To solve this problem, a novel method for random noise suppression based on cross correlation is proposed in this manuscript. According to the characteristics of the MRS signal, a sinusoidal signal is constructed as a reference signal, which has the same frequency as Larmor frequency. It shows a strong correlation with the MRS signal, while demonstrating minimal correlation with the random noise. In terms of this property, the cross correlation is used to recover the MRS signal from random noise interference. By convolving the noisy signal with the reference signal and deconvolving the processed convolution waveform, the desired MRS signal is acquired. In order to validate the efficiency of the denoising strategy, numerical simulations on the synthetic signals embedded in different noise levels are performed, and the uncertainties of the estimated signal parameters are compared. In addition, the cross correlation method is applied following a standard processing scheme in field data, also resulting in improved SNRs. The cross correlation algorithm may achieve better denoising results than the commonly used denoising method with fewer filtering parameters and less human labor.