Hilbert-Huang变换与傅里叶变换在大地电磁数据处理中的适用性分析

发布时间：2018-04-13 02:18

本文选题：傅立叶变换 + Hilbert-Huang变换　；参考：《地球物理学进展》2017年04期

【摘要】：Hilbert-Huang变换(HHT)和傅立叶变换是目前广发应用于大地电磁(MT)信号处理的两种算法,但两种方法在MT信号的处理中的适用性研究却鲜有报道.文章以仿真平稳信号、加噪信号、非平稳信号和实测大地电磁信号为例,从准确性、稳定性、计算效率等几个方面比较了两种算法在大地电磁信号处理中的适用性.结果表明:傅立叶变换对于无噪平稳信号的分析,其分辨率和准确性很高,且计算速度快,适合海量大地电磁测深数据的处理;HHT算法具有时频分析和滤除高频分量的能力,能精确的刻画信号能量随时间和频率的分布,且抗噪声性能好,在MT数据筛选和去噪等方面有优势;基于HHT边际谱的功率谱估计更适合MT信号非平稳特性的实质,但其计算效率低,是制约其工程应用的瓶颈问题.
[Abstract]:Hilbert-Huang transform and Fourier transform are two algorithms which are widely used in magnetotelluric (MT) signal processing, but the applicability of the two methods in MT signal processing is seldom reported.Taking the simulated stationary signal, noised signal, non-stationary signal and measured magnetotelluric signal as examples, the applicability of the two algorithms in magnetotelluric signal processing is compared in terms of accuracy, stability and computational efficiency.The results show that the Fourier transform has high resolution and accuracy for noiseless stationary signal analysis, and the calculation speed is fast. The HHT algorithm is suitable for the processing of massive magnetotelluric sounding data and has the ability of time-frequency analysis and filtering of high-frequency components.It can accurately describe the distribution of signal energy with time and frequency, and has good anti-noise performance, so it has advantages in MT data filtering and denoising, and the power spectrum estimation based on HHT marginal spectrum is more suitable for the essence of non-stationary characteristics of MT signal.But its calculation efficiency is low, is the bottleneck problem which restricts its engineering application.
【作者单位】：湖南文理学院洞庭湖生态经济区建设与发展湖南省协同创新中心;湖南财政经济学院信息技术与管理学院;
【基金】：国家自然科学基金项目(41304098) 湖南省自然科学基金项目(2017JJ2192,2017JJ2015) 湖南省教育厅重点项目(16A146)联合资助
【分类号】：P631.325

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