A combinatorial filtering method for magnetotelluric data series with strong interference
A combinatorial filtering method for magnetotelluric data series with strong interference
复制标题
强干扰大地电磁数据序列的组合滤波方法
DOI：
10.1007/s12517-016-2658-5
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发表时间：
2016-09
影响因子：
--
通讯作者：
蔡剑华Cai Jian-hua
中科院分区：
文献类型：
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作者：
蔡剑华Cai Jian-hua
在高度工业化地区，大地电磁（MT）引起的变化被强人为噪声信号污染。一种方法被描述为用于噪声去除的替代方法，基于经验模式分解（EMD）与独立分量分析（ICA）的组合。过滤过程利用了这样一个事实，即通过不同的尺度级别分析数据，这需要最少的人为干预，并保持良好的数据部分不变。讨论了该方法的原理和步骤，并通过一些参数对去噪效果进行了评价。在滤波阶段之后，在频域中处理数据以产生两组可靠的MT传递函数，并且将结果与EMD-小波方法的结果进行比较。对模拟信号和实测MT数据序列进行了处理。结果表明，该工艺处理后的视电阻率和相位曲线有较大改善。点缺陷被过滤掉，以消除它们的有害影响，这产生可靠的估计MT传递函数。EMD-ICA方法为低信噪比条件下MT数据序列的去噪提供了一种新的方法。
In highly industrialized areas, magnetotelluric (MT)-induced variations are contaminated by strong manmade noise signals. A method is described as an alternative approach for noise removal, based on a combination of empirical mode decomposition (EMD) with independent component analysis (ICA). The filtering procedure takes advantage of the fact that data are analyzed through different scale levels, which requires a minimum of human intervention and leaves good data sections unchanged. Principle and steps of method are discussed, and de-noising results are evaluated by some parameters. After the filtering stage, data is processed in the frequency domain to yield two sets of reliable MT transfer functions and the result was compared with that of the EMD-Wavelet method. Simulated signal and measured MT data series are processed. The results show that this procedure can lead to greatly improved apparent resistivity and phase curves after processing. Point defects are filtered out to eliminate their deleterious influence, which yields reliable estimates of the MT transfer functions. The EMD-ICA method provides a new method for the de-noising of MT data series under the condition of low SNR.
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DOI：
--
发表时间：
2004
期刊：
--
影响因子：
--
作者：
Wang Bing-xi
通讯作者：
Wang Bing-xi
影响因子：
2.8
作者：
R. Banks
通讯作者：
R. Banks
影响因子：
7.8
作者：
Hyvärinen, A;Oja, E
通讯作者：
Oja, E
DOI：
--
发表时间：
2007
期刊：
--
影响因子：
--
作者：
Li Hong
通讯作者：
Li Hong
DOI：
10.1109/icassp.2001.940210
发表时间：
2001-05
期刊：
2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221)
影响因子：
--
作者：
F. Asano;Shiro Ikeda;Michiaki Ogawa;H. Asoh;N. Kitawaki
通讯作者：
F. Asano;Shiro Ikeda;Michiaki Ogawa;H. Asoh;N. Kitawaki