Parameter Estimation of Surface Nuclear Magnetic Resonance Signals Based on Total Least Squares-Estimation of Signal Parameters via Rotational Invariance Technique
In the Surface Nuclear Magnetic Resonance (SNMR) water searching system, the parameters of SNMR signals can be used to predict the water storage, electrical conductivity, pore structure of underground aquifer. However, the SNMR signals collected on site are very weak in practical application, which is easy to be interfered by environmental noise, resulting in the inability to directly obtain the parameters of SNMR signal. To solve this problem, an estimation method of SNMR signal parameters based on Total Least Squares-Estimation of Signal Parameters via Rotational Invariance Technique (TLS-ESPRIT) is proposed in this paper. Based on the similar signal characteristics of harmonic noise and SNMR signals, a mixed signal model consisting of multiple sinusoidal attenuation signals is constructed. TLS-ESPRIT is used to transform the problem of extracting mixed signal parameters into a generalized eigenvalue solution of a rotation invariant matrix, in order to obtain the Lamor frequency and the relaxation time of the SNMR signal, and its initial amplitude and phase are obtained by combining the least squares method. The experimental results of simulated signal and measured signal show that the proposed method can estimate the parameters of SNMR signal mixed with random noise and power frequency harmonic noise. Compared with the traditional harmonic modeling method, the parameter extraction accuracy is better.
Surface Nuclear Magnetic Resonance (SNMR)Total Least Squares-Estimation of Signal Parameters via Rotational Invariance Technique (TLS-ESPRIT)Harmonic noise
万方数据
维普
