基于经验模态分解的 MT 数据脉冲类电磁噪声处理

摘要

电磁脉冲干扰是大地电磁测深系统（M T ）信号的主要噪声之一，严重影响后续视电阻率和阻抗的计算及目标信息的提取。针对脉冲类噪声在时间域中的变化特征，利用经验模态分解（EMD）对脉冲类电磁噪声进行压制处理。首先，对大地电磁信号经EMD分解后得到 N个本征模态函数（IM F）；然后，对每一阶的IM F选择一个合适的阀值，对于该IM F中超出该阀值的部分进行截断；最后，进行EM D重构。实测数据测试表明：改正后信号能量损失小，与改正前信号相关性高，可有效地抑制脉冲类噪声干扰。%As one of the main noise interferences of the magnetotelluric sounding system (M T ) , like-impulse electromagnetic noise not only affects the count of subsequent apparent resistivity and impedance , but also badly influences the target information extraction . In this paper ,we briefly introduced the basic principles and algorithms of the empirical mode decomposition method (EMD) ,and based on the analysis of actual data ,we discussed its application in magnetotelluric signal processing and noise suppression .First ,we can get intrinsic mode function (IMF) after EMD decomposition from magnetotelluric signal ;then ,select a suitable threshold for each of the IM F and truncated the excess part ;last ,did EMD reconstruction .Test results of field data show that corrected signal is of high correlation coefficient and less energy loss compared with raw signal , and is a high accuracy approximation of raw signal .T he like-impulse noise of field data can be restrained efficiently .