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为提高大地电磁数据的信噪比，笔者提出基于互补总体经验模式分解 （ＣＥＥＭＤ） 和自适应中值滤波的去噪方法，利用 ＣＥＥＭＤ将大地电磁时间序列数据分解成多个固有模态函数 （ＩＭＦ）及趋势项，依据噪声的高低频特征有选择地利用自适应中值滤波对固有模态函数 （ＩＭＦ）进行去噪，再进行数据重构。对实测数据进行处理，该方法能较好地抑制大地电磁数据中、低频部分的噪声干扰，抑制突变点，提高数据的信噪比。
In order to improve the signal-to-noise ratio of magnetotelluric data in the earth, the author proposes a denoising method based on complementary total empirical mode decomposition (CEEMD) and adaptive median filtering, and decomposes the geomagnetic time series data into multiple intrinsic mode functions ) And trend term, the adaptive median filter is used selectively to denoise the intrinsic mode function (IMF) according to the high and low frequency features of the noise, and then the data reconstruction. The measured data processing, the method can better restrain the electromagnetic interference in the low-frequency part of the earth electromagnetic data, restrain the mutation point, and improve the signal to noise ratio of the data.