基于压缩感知重构算法和形态滤波的AMT近源干扰压制（英文）

Near-source noise suppression of AMT by compressive sensing and mathematical morphology filtering

进行音频大地电磁法勘探时不可避免的受到近源干扰的影响,限制了该方法的勘探深度。形态滤波法已被证明对于不同形态的大尺度强干扰(通常为低频噪声)有明显的压制作用,但是对于窄脉冲噪声无能为力,为此本文提出一种基于压缩感知重构算法和形态滤波法的近源干扰压制方法(简称MMF-IOMP法),即首先使用形态滤波法滤除大尺度的强干扰,然后采用改进的正交匹配追踪算法进一步滤除形态滤波法残留的类脉冲噪声。为滤除残留的类脉冲噪声并保留AMT有效信号,我们构造了只对类脉冲噪声敏感而对有效部分不敏感的冗余字典。仿真实验以及庐枞矿集区实测数据处理结果表明,所述方法能够克服形态滤波法对于脉冲干扰处理效果不佳以及单一的信号重构算法耗时过长的缺点,在较好的保留有用信号的前提下有效压制音频大地电磁信号中的近源效应。

In deep mineral exploration, the acquisition of audio magnetotelluric （AMT） data is severely affected by ambient noise near the observation sites; This near-field noise restricts investigation depths. Mathematical morphological filtering （MMF） proved effective in suppressing large-scale strong and variably shaped noise, typically low-frequency noise, but can not deal with pulse noise of AMT data. We combine compressive sensing and MMF. First we use MMF to suppress the large-scale strong ambient noise; second, we use the improved orthogonal match pursuit （IOMP） algorithm to remove the residual pulse noise. To remove the noise and protect the useful AMT signal, a redundant dictionary that matches with spikes and is insensitive to the useful signal is designed. Synthetic and field data from the Luzong field suggest that the proposed method suppresses the near-source noise and preserves the signal well; thus, better results are obtained that improve the output of either MMF or IOMP.