期刊文献+
共找到1篇文章
< 1 >
每页显示 20 50 100
Near-source noise suppression of AMT by compressive sensing and mathematical morphology filtering 被引量:31
1
作者 Li Guang Xiao Xiao +4 位作者 Tang Jing-Tian Li Jin Zhu Hui-Jie Zhou Cong Yan Fa-Bao 《Applied Geophysics》 SCIE CSCD 2017年第4期581-589,623,共10页
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 m... 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. 展开更多
关键词 Compressive sensing FILTERING magnetoiellurics signal processing noise
下载PDF
上一页 1 下一页 到第
使用帮助 返回顶部