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）
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摘要
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.
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.
引文
Bollig,A.,Disch,C.,Arts,M.,et al.,2017,SNR walls in eigenvalue-based spectrum sensing:Eurasip Journal onWireless Communications&Networking,2017(1),109.
Cai,J.H.,Tang,J.T.,Hua,X.R.,et al.,2009,An analysis method for magnetotelluric data based on the HilbertHuang Transform:Exploration Geophysics,40(2),197-205.
Candes,E.J.,Romberg,J.,and Tao,T.,2006,Robust uncertainty principles:Exact signal reconstruction from highly incomplete frequency information:IEEE Transactions on Information Theory,52(2),489-509.
Candès,E.J.,and Tao,T.,2006,Near-optimal signal recovery from random projections:Universal encoding strategies:IEEE transactions on information theory,52(12),5406-5425.
Candes,E.J.,and Wakin,M.B.,2008,An introduction to compressive sampling:Signal Processing Magazine,IEEE,25(2),21-30.
Dai,W.,and Milenkovic,O.,2009,Subspace pursuit for compressive sensing signal reconstruction:IEEE Transactions on Information Theory,55(5),2230-42249.
Davenport,M.A.,and Wakin,M.B.,2010,Analysis of orthogonal matching pursuit using the restricted isometry property:IEEE Transactions on Information Theory,56(9),4395-4401.
Donoho,D.L.,2006,Compressed sensing:IEEE Transactions on information theory,52(4),1289-1306.
Duarte,M.F.,Davenport,M.A.,Takhar,D.,et al.,2008,Single-pixel imaging via compressive sampling:IEEE Signal Processing Magazine,25(2),83-91.
Egbert,G.D.,1997,Robust multiple-station magnetotelluric data processing:Geophysical Journal International,130(2),475-496.
Gamble,T.D.,Goubau,W.M.,and Clarke,J.,1979,Magnetotellurics with a remote magnetic reference:Geophysics,44(1),53-68.
Garcia,X.,and Jones,A.G.,2008,Robust processing of magnetotelluric data in the AMT dead band using the continuous wavelet transform:Geophysics,73(6),F223-F234.
Guo,H.Y.,Yang,Z.,and Zhu,W.P.,2012,Anewsinglechannel speech separation method based on sparse decomposition:Acta Electronica Sinica,40(4),762-768.
Hennenfent,G.,and Herrmann,F.J.,2008,Simply denoise:Wavefield reconstruction via jittered undersampling:Geophysics,73(3),V19-V28.
Huang,H.,and Makur,A.,2011,Backtracking-based matching pursuit method for sparse signal reconstruction:IEEE Signal Processing Letters,18(7),391-394.
Jin,J.,Gu,Y.T.,and Mei,S.L.,2010,An Introduction to Compressive Sampling and Its Applications:Journal of Electronics&Information Technology,32(2),470-475.
Li,F.L.,Chang,J.,Zhang,X.Y.,et al.,2015,Reconstruction algorithm of blind sparse and its de-noising application in speech based on compressed sensing:Journal of Central South University,46(1),164-170.
Li,G.,Tang,J.T.,Wen,S.S.,et al.,2017,Suppression of strong noise in MT data based on reconstruction algorithm of compressive sensing:International Geophysical Conference,17-20 April,Qingdao,China,497-499.
Li,J.,Tang,J.T.,Wang,L.,et al.,2014,Noise suppression for magnetotelluric sounding data based on signal subspace enhancement and endpoint detection:Acta Physica Sinica,63(1),247-254.
Li,Q.,Han,L.G.,Chen,J.Y.,et al.,2015,Separation of inhomogeneous blended seismic data:Applied Geophysics,12(3),327-333.
Li,S.T.,and Wei,D.,2009,A Survey on Compressive Sensing:Acta Automatica Sinica,35(11),1369-1377.
Liu,Y.X.,Zhao,R.Z.,Hu,S.H.,et al.,2010,Regularized Adaptive Matching Pursuit Algorithm for Signal Reconstruction Basedon Compressive Sensing:Journal of Electronics&Information Technology,32(11),2713-2717.
Matheron,G.,and Serra,J.,2000,The Birth of Mathematical Morphology:Proceedings of the 5th International Symposium on Mathematical Morphology and its Applications to Image and Signal Processing,ISMM2000,Palo Alto,CA,USA,June 26-28.
Mallat,S.G.,and Zhang,Z.,1993,Matching pursuits with time-frequency dictionaries:IEEE Transactions on signal Processing,41(12),3397-3415.
Needell,D.,and Tropp,J.A.,2009,CoSaMP:Iterative signal recovery from incomplete and inaccurate samples:Applied and Computational Harmonic Analysis,26(3),301-321.
Pati,Y.C.,Rezaiifar,R.,and Krishnaprasad,P.S.,1993,Orthogonal matching pursuits:Recursive function approximation with applications to wavelet decomposition:Proceedings of the 27th Asilomar Conference in Signals,Systems,and Computers.
Ren,Z.,Kalscheuer,T.,Greenhalgh,S.,et al.,2013,A goaloriented adaptive finite-element approach for plane wave3-D electromagnetic modelling:Geophysical Journal International,194(2),700-718.
Shireesha,M.,and Harinarayana,T.,2011,Processing of magnetotelluric data-a comparative study with 4 and 6element impedance tensor elements:Applied Geophysics,8(4),285-292.
Shi,G.M.,Liu,D.H.,Gao,D.H.,et al.,2009,Advances in theory and application of compressed sensing:Acta Electronica Sinica,37(5),10701-1081.
Smirnov,M.Y.,2003,Magnetotelluric data processing with a robust statistical procedure having a high breakdown point:Geophysical Journal International,152(1),1-7.
Tang,G.,Ma,J.W.,and Yang,H.Z.,2012a,Seismic data denoising based on learning-type overcomplete dictionaries:Applied Geophysics,9(1),27-32.
Tang,J.T.,Hua,X.R.,Cao,Z.M.,et al.,2008,HilbertHuang transformation and noise suppression of magnetotelluric sounding data:Chinese J.Geophys(in Chinese),51(2),603-610.
Tang,J.T.,Li,H.,Li,J.,et al.,2014,Top-Hat transformation and magnetotelluric sounding data strong interference separation of Lijiang-Zongyang ore concentration area:Journal of Jilin University(Earth Science Edition)(in Chinese),44(1),336-343.
Tang,J.T.,Li,J.,Xiao,X.,et al.,2012b,Mathematical morphology filtering an noise suppression of magnetotelluric sounding data:Chinese J.Geophys(in Chinese),55(05),1784-1793.
Tang,J.T.,Liu,Z.J.,Liu,F.Y.,et al.,2015,The denoising of the audio magnetotelluric data set with strong interferences:Chinese J.Geophys(in Chinese),58(12),4636-4647.
Tang,J.T.,Xu,Z.M.,Xiao,X.,et al.,2012c,Effect rules of strong noise on magnetotelluric(MT)sounding in the Luzong ore cluster area:Chinese J.Geophys(in Chinese),55(12),4147-4159.
Tang,J.T.,Zhou,C.,Wang,X.Y.,et al.,2013,Deep electrical structure and geological significance of Tongling ore district:Tectonophysics,606,78-96.
Trad,D.O.,and Travassos,J.M.,2000,Wavelet filtering of magnetotelluric data:Geophysics,65(2),482-491.
Tropp,J.A.,and Gilbert,A.C.,2007,Signal recovery from random measurements via orthogonal matching pursuit:IEEE Transactions on Information Theory,53(12),4655-4666.
Wang,X.,Zhu,H.,Rui,T.,et al.,2015,Shift invariant sparse coding ensemble and its application in rolling bearing fault diagnosis:Journal of Vibroengineering,17(4),1837-1848.
Xiao,X.,Tang,J.T.,Zhou,C.,et al.,2011,Magnetotelluric sounding in the Lujiang-Zongyang ore district and preliminary study of electrical structure:Acta Geological Sinica(in Chinese),85(5),873-886.
Zhang,H.,Chen,X.H.,and Zhang,L.Y.,2017,3D simultaneous seismic data reconstruction and noise suppression based on the curvelet transform:Applied Geophysics,14(1),87-95.
Zhu,H.J.,Wang,X.Q.,Rui,T.,et al.,2015,Implication of improved matching pursuit in de-noising for square wave:Journal of PLA University of Science and Technology(Natural Science Edition)(in Chinese),16(4),305-309.
Cai,J.H.,Tang,J.T.,Hua,X.R.,et al.,2009,An analysis method for magnetotelluric data based on the HilbertHuang Transform:Exploration Geophysics,40(2),197-205.
Candes,E.J.,Romberg,J.,and Tao,T.,2006,Robust uncertainty principles:Exact signal reconstruction from highly incomplete frequency information:IEEE Transactions on Information Theory,52(2),489-509.
Candès,E.J.,and Tao,T.,2006,Near-optimal signal recovery from random projections:Universal encoding strategies:IEEE transactions on information theory,52(12),5406-5425.
Candes,E.J.,and Wakin,M.B.,2008,An introduction to compressive sampling:Signal Processing Magazine,IEEE,25(2),21-30.
Dai,W.,and Milenkovic,O.,2009,Subspace pursuit for compressive sensing signal reconstruction:IEEE Transactions on Information Theory,55(5),2230-42249.
Davenport,M.A.,and Wakin,M.B.,2010,Analysis of orthogonal matching pursuit using the restricted isometry property:IEEE Transactions on Information Theory,56(9),4395-4401.
Donoho,D.L.,2006,Compressed sensing:IEEE Transactions on information theory,52(4),1289-1306.
Duarte,M.F.,Davenport,M.A.,Takhar,D.,et al.,2008,Single-pixel imaging via compressive sampling:IEEE Signal Processing Magazine,25(2),83-91.
Egbert,G.D.,1997,Robust multiple-station magnetotelluric data processing:Geophysical Journal International,130(2),475-496.
Gamble,T.D.,Goubau,W.M.,and Clarke,J.,1979,Magnetotellurics with a remote magnetic reference:Geophysics,44(1),53-68.
Garcia,X.,and Jones,A.G.,2008,Robust processing of magnetotelluric data in the AMT dead band using the continuous wavelet transform:Geophysics,73(6),F223-F234.
Guo,H.Y.,Yang,Z.,and Zhu,W.P.,2012,Anewsinglechannel speech separation method based on sparse decomposition:Acta Electronica Sinica,40(4),762-768.
Hennenfent,G.,and Herrmann,F.J.,2008,Simply denoise:Wavefield reconstruction via jittered undersampling:Geophysics,73(3),V19-V28.
Huang,H.,and Makur,A.,2011,Backtracking-based matching pursuit method for sparse signal reconstruction:IEEE Signal Processing Letters,18(7),391-394.
Jin,J.,Gu,Y.T.,and Mei,S.L.,2010,An Introduction to Compressive Sampling and Its Applications:Journal of Electronics&Information Technology,32(2),470-475.
Li,F.L.,Chang,J.,Zhang,X.Y.,et al.,2015,Reconstruction algorithm of blind sparse and its de-noising application in speech based on compressed sensing:Journal of Central South University,46(1),164-170.
Li,G.,Tang,J.T.,Wen,S.S.,et al.,2017,Suppression of strong noise in MT data based on reconstruction algorithm of compressive sensing:International Geophysical Conference,17-20 April,Qingdao,China,497-499.
Li,J.,Tang,J.T.,Wang,L.,et al.,2014,Noise suppression for magnetotelluric sounding data based on signal subspace enhancement and endpoint detection:Acta Physica Sinica,63(1),247-254.
Li,Q.,Han,L.G.,Chen,J.Y.,et al.,2015,Separation of inhomogeneous blended seismic data:Applied Geophysics,12(3),327-333.
Li,S.T.,and Wei,D.,2009,A Survey on Compressive Sensing:Acta Automatica Sinica,35(11),1369-1377.
Liu,Y.X.,Zhao,R.Z.,Hu,S.H.,et al.,2010,Regularized Adaptive Matching Pursuit Algorithm for Signal Reconstruction Basedon Compressive Sensing:Journal of Electronics&Information Technology,32(11),2713-2717.
Matheron,G.,and Serra,J.,2000,The Birth of Mathematical Morphology:Proceedings of the 5th International Symposium on Mathematical Morphology and its Applications to Image and Signal Processing,ISMM2000,Palo Alto,CA,USA,June 26-28.
Mallat,S.G.,and Zhang,Z.,1993,Matching pursuits with time-frequency dictionaries:IEEE Transactions on signal Processing,41(12),3397-3415.
Needell,D.,and Tropp,J.A.,2009,CoSaMP:Iterative signal recovery from incomplete and inaccurate samples:Applied and Computational Harmonic Analysis,26(3),301-321.
Pati,Y.C.,Rezaiifar,R.,and Krishnaprasad,P.S.,1993,Orthogonal matching pursuits:Recursive function approximation with applications to wavelet decomposition:Proceedings of the 27th Asilomar Conference in Signals,Systems,and Computers.
Ren,Z.,Kalscheuer,T.,Greenhalgh,S.,et al.,2013,A goaloriented adaptive finite-element approach for plane wave3-D electromagnetic modelling:Geophysical Journal International,194(2),700-718.
Shireesha,M.,and Harinarayana,T.,2011,Processing of magnetotelluric data-a comparative study with 4 and 6element impedance tensor elements:Applied Geophysics,8(4),285-292.
Shi,G.M.,Liu,D.H.,Gao,D.H.,et al.,2009,Advances in theory and application of compressed sensing:Acta Electronica Sinica,37(5),10701-1081.
Smirnov,M.Y.,2003,Magnetotelluric data processing with a robust statistical procedure having a high breakdown point:Geophysical Journal International,152(1),1-7.
Tang,G.,Ma,J.W.,and Yang,H.Z.,2012a,Seismic data denoising based on learning-type overcomplete dictionaries:Applied Geophysics,9(1),27-32.
Tang,J.T.,Hua,X.R.,Cao,Z.M.,et al.,2008,HilbertHuang transformation and noise suppression of magnetotelluric sounding data:Chinese J.Geophys(in Chinese),51(2),603-610.
Tang,J.T.,Li,H.,Li,J.,et al.,2014,Top-Hat transformation and magnetotelluric sounding data strong interference separation of Lijiang-Zongyang ore concentration area:Journal of Jilin University(Earth Science Edition)(in Chinese),44(1),336-343.
Tang,J.T.,Li,J.,Xiao,X.,et al.,2012b,Mathematical morphology filtering an noise suppression of magnetotelluric sounding data:Chinese J.Geophys(in Chinese),55(05),1784-1793.
Tang,J.T.,Liu,Z.J.,Liu,F.Y.,et al.,2015,The denoising of the audio magnetotelluric data set with strong interferences:Chinese J.Geophys(in Chinese),58(12),4636-4647.
Tang,J.T.,Xu,Z.M.,Xiao,X.,et al.,2012c,Effect rules of strong noise on magnetotelluric(MT)sounding in the Luzong ore cluster area:Chinese J.Geophys(in Chinese),55(12),4147-4159.
Tang,J.T.,Zhou,C.,Wang,X.Y.,et al.,2013,Deep electrical structure and geological significance of Tongling ore district:Tectonophysics,606,78-96.
Trad,D.O.,and Travassos,J.M.,2000,Wavelet filtering of magnetotelluric data:Geophysics,65(2),482-491.
Tropp,J.A.,and Gilbert,A.C.,2007,Signal recovery from random measurements via orthogonal matching pursuit:IEEE Transactions on Information Theory,53(12),4655-4666.
Wang,X.,Zhu,H.,Rui,T.,et al.,2015,Shift invariant sparse coding ensemble and its application in rolling bearing fault diagnosis:Journal of Vibroengineering,17(4),1837-1848.
Xiao,X.,Tang,J.T.,Zhou,C.,et al.,2011,Magnetotelluric sounding in the Lujiang-Zongyang ore district and preliminary study of electrical structure:Acta Geological Sinica(in Chinese),85(5),873-886.
Zhang,H.,Chen,X.H.,and Zhang,L.Y.,2017,3D simultaneous seismic data reconstruction and noise suppression based on the curvelet transform:Applied Geophysics,14(1),87-95.
Zhu,H.J.,Wang,X.Q.,Rui,T.,et al.,2015,Implication of improved matching pursuit in de-noising for square wave:Journal of PLA University of Science and Technology(Natural Science Edition)(in Chinese),16(4),305-309.