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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.
Hilbert-Huang Transform (HHT) and Fourier Transform are two algorithms applied to MT signal processing at present, but the applicability of the two methods in the processing of MT signal is seldom reported.In this paper, Signal, noise signal, non-stationary signal and measured magnetotelluric signal as examples, the applicability of the two algorithms in the electromagnetic signal processing is compared from several aspects such as accuracy, stability, computational efficiency, etc. The results show that the Fourier transform For the analysis of the no-noise and steady signal, its resolution and accuracy are high, and the calculation speed is fast, so it is suitable for the processing of the massive earth electromagnetic sounding data. The HHT algorithm has the ability of time-frequency analysis and high frequency component filtering, The signal energy distribution with time and frequency is characterized, and the anti-noise performance is good, which has advantages in MT data screening and denoising. The power spectrum estimation based on HHT marginal spectrum is more suitable for the non-stationary characteristics of MT signal, but its computational efficiency Low, is the bottleneck restricting its engineering applications.