Separation of magnetotelluric signals based on refined composite multiscale dispersion entropy and orthogonal matching pursuit

Separation of magnetotelluric signals based on refined composite multiscale dispersion entropy and orthogonal matching pursuit | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Full paper Separation of magnetotelluric signals based on refined composite multiscale dispersion entropy and orthogonal matching pursuit Xian Zhang, Jin Li, Diquan Li, Yong Li, Bei Liu, Yanfang Hu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-53570/v2 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 23 Mar, 2021 Read the published version in Earth, Planets and Space → Version 2 posted 9 You are reading this latest preprint version Show more versions Abstract Magnetotelluric (MT) data processing can increase the reliability of measured data. Traditional MT de-noising methods are usually filtered in entire MT time-series sequence, which result in losing of useful MT signals and the decrease of imaging accuracy of electromagnetic inversion. However, targeted MT noise separation can retain the part of data not affected by strong noise, and enhance the quality of MT data. Thus, we proposed a novel method for MT noise separation, which using refined composite multiscale dispersion entropy (RCMDE) and orthogonal matching pursuit (OMP). Firstly, the RCMDE characteristic parameters are extracted from each segment of the MT time-series. Then, the characteristic parameters are input to the fuzzy c-mean (FCM) clustering for automatic identification of MT signal and noise. Next, OMP method is utilized to remove the identified noise segments independently. Finally, the reconstructed signal consists of the denoised data segments and the identified useful signal segments. We conducted the simulation experiments and algorithm evaluation on the EMTF data, simulated data and measured sites. The results indicate that the RCMDE can improve the stability of multiscale dispersion entropy (MDE) and multiscale entropy (MSE) by analyzing the characteristics of the signal samples library, effectively dividing MT signals and noise. Compared with the existing techniques of the entire time domain de-noising and signal-noise identification, the proposed method used RCMDE and OMP as characteristic parameter and noise separation, simplified the multi-features fusion, and improved the accuracy of signal-noise identification. Moreover, the de-noising efficiency has accelerated, and the MT data quality of low-frequency band has improved greatly. Geology Electrophysics magnetotelluric (MT) refined composite multiscale dispersion entropy (RCMDE) orthogonal matching pursuit (OMP) noise separation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Full Text Supplementary Files GraphicalAbstract.jpg Cite Share Download PDF Status: Published Journal Publication published 23 Mar, 2021 Read the published version in Earth, Planets and Space → Version 2 posted Editorial decision: Major Revision 18 Jan, 2021 Review # 2 received at journal 17 Jan, 2021 Reviewer # 2 agreed at journal 04 Jan, 2021 Editor assigned by journal 22 Dec, 2020 Reviewers invited by journal 22 Dec, 2020 Reviewer # 1 agreed at journal 22 Dec, 2020 Review # 1 received at journal 22 Dec, 2020 Submission checks completed at journal 22 Dec, 2020 Editor invited by journal 22 Dec, 2020 You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-53570","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Full paper","associatedPublications":[],"authors":[{"id":7096898,"identity":"16462848-65a7-4765-b999-1b2610529b3f","order_by":0,"name":"Xian Zhang","email":"","orcid":"https://orcid.org/0000-0001-9156-9742","institution":"Central South University School of Geosciences and Info Physics","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xian","middleName":"","lastName":"Zhang","suffix":""},{"id":7096899,"identity":"9716e6ea-4232-4aee-8fec-b76191d709d7","order_by":1,"name":"Jin Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0UlEQVRIiWNgGAWjYHACxgNAQoaxvbHx4Qdi9YC08DD2HG42liBJC4NEepsADzHK5d2bDxz48OswD/PMh20MEgx2croNBLQYnjmWcHBm32EextmJbQ8KGJKNzQ4Q0jIjx+Awbw9YS7uBBMOBxG0Etcx/A9Uy82CbBA8xWuQleAwO8/wAapnBSKQWA540oF8a0oGBnAgMZAMi/CLffvjggw9/rOUM248/fPihwk6OoBYDkALGtmYGwwYwl4BysC1glX/qGOSJUDwKRsEoGAUjFAAAnsxJPeVQwKMAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0001-6606-6967","institution":"","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Jin","middleName":"","lastName":"Li","suffix":""},{"id":7096900,"identity":"93edc2aa-5fe1-4219-85ac-07832d47ff0e","order_by":2,"name":"Diquan Li","email":"","orcid":"","institution":"Central South University School of Geosciences and Info Physics","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Diquan","middleName":"","lastName":"Li","suffix":""},{"id":7096901,"identity":"d5be8934-6c80-44a9-9f1f-b9ce1c573013","order_by":3,"name":"Yong Li","email":"","orcid":"","institution":"Chinese Academy of Geological Sciences Institute of Geophysical and Geochemical Exploration","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yong","middleName":"","lastName":"Li","suffix":""},{"id":7096902,"identity":"a75d0ed8-9d40-42ce-8533-5a14e8b98f21","order_by":4,"name":"Bei Liu","email":"","orcid":"","institution":"Hunan University Art and Science College of Mathematics and Physics","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Bei","middleName":"","lastName":"Liu","suffix":""},{"id":7096903,"identity":"cddfad1e-1096-494d-837d-6dd8e11696df","order_by":5,"name":"Yanfang Hu","email":"","orcid":"","institution":"Central South University School of Geosciences and Info Physics","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yanfang","middleName":"","lastName":"Hu","suffix":""}],"badges":[],"createdAt":"2020-08-04 11:57:16","currentVersionCode":2,"declarations":"","doi":"10.21203/rs.3.rs-53570/v2","doiUrl":"https://doi.org/10.21203/rs.3.rs-53570/v2","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s40623-021-01399-z","type":"published","date":"2021-03-23T15:00:31+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":4785042,"identity":"7d7731f1-028b-478c-b4de-fe0de7cf3f72","added_by":"auto","created_at":"2021-01-07 18:27:59","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":112238,"visible":true,"origin":"","legend":"The results obtained for (a)MSE, (b)MDE and (c)RCMDE using a set of sample library signals at different scale factor, among them, the abscissa represents the scale factor , and the ordinate represents the entropy value at the corresponding scale.","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-53570/v2/acd23a46d72ccb4e024e7a0d.jpg"},{"id":4785241,"identity":"f329bec7-39b3-4b02-8896-e648798d8a82","added_by":"auto","created_at":"2021-01-07 18:30:59","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":156550,"visible":true,"origin":"","legend":"The de-noising effect and frequency spectrum analysis of the noisy signal with (a) matching pursuit (MP) and (b) orthogonal matching pursuit (OMP).","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-53570/v2/1f927075e4fb25836152c977.jpg"},{"id":4785762,"identity":"c85ca2c4-d9a0-4c28-9ffe-f4e5035b2d57","added_by":"auto","created_at":"2021-01-07 18:36:59","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":163705,"visible":true,"origin":"","legend":"FCM clustering effect of sample library signals. Among them, characteristic X and Y in the coordinate axis represent the refined composite multiscale dispersion entropy (RCMDE) value when the scale factor is 1 and 2, respectively.","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-53570/v2/7172beda5df1d23f5f60fc08.jpg"},{"id":4785044,"identity":"a9a5b841-3604-4eb7-a6e4-90856d9007a3","added_by":"auto","created_at":"2021-01-07 18:27:59","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":121165,"visible":true,"origin":"","legend":"The EMTF data is disturbed by a noisy signal with (a) square wave interference of Hx and (b) charge and discharge triangle wave interference of Ey; (c) is a comparison of the apparent resistivity-phase curves, left figure curve is and right figure curve is . Among them, curve 1 is original data, curve 2 is noisy data, curve 3 is remote reference method, curve 4 is OMP-based overall method, and curve 5 is the proposed method.","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-53570/v2/eaddb090cb0ce66a0ebd48a3.jpg"},{"id":4785372,"identity":"1306530c-5ab5-4ee0-a6bd-b3f2e1ed0f40","added_by":"auto","created_at":"2021-01-07 18:33:59","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":100530,"visible":true,"origin":"","legend":"The signal-noise identification and targeted de-noising for the measured MT data, and compared with the OMP method-based overall method and the proposed method, (a) square wave interference and (b) triangle wave interference.","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-53570/v2/99cbe038d08856d92ea04dfe.jpg"},{"id":4785245,"identity":"be225546-fd4c-4924-bd5d-b78b137f35e2","added_by":"auto","created_at":"2021-01-07 18:30:59","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":124840,"visible":true,"origin":"","legend":"Comparison of the apparent resistivity-phase curves of the measured MT site D37890, among them, curve 1 is original data, curve 2 is the data filtered by the OMP method-based overall method, curve 3 is the result derived from the fractal-entropy and clustering method, and curve 4 is the result derived from the proposed method.","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-53570/v2/df16bccd0063a16bdb31bbe1.jpg"},{"id":4785049,"identity":"3edc65b3-7691-4ede-99c7-fa2d2d31a644","added_by":"auto","created_at":"2021-01-07 18:27:59","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":123859,"visible":true,"origin":"","legend":"Comparison of the apparent resistivity-phase curves of the measured AMT site (a) EL22189 and (b) EL22174, among them, curve 1 is original data, curve 2 is the result obtained by the remote reference (RR) method, curve 3 is the data filtered by the OMP method-based overall method, curve 4 is the result derived from the fractal-entropy and clustering method, and curve 5 is the result derived from the proposed method.","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-53570/v2/1fe9d9a98a016d822c07e312.jpg"},{"id":4785370,"identity":"b53cec1e-a706-47bb-a8bf-1d4fc309e8e0","added_by":"auto","created_at":"2021-01-07 18:33:59","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":139586,"visible":true,"origin":"","legend":"Comparison of the polarization direction for site EL22174, (a) electric field data at 0.3 Hz, and (b) magnetic field data at 4 Hz.","description":"","filename":"8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-53570/v2/1b5d1f8c29a31a1e921d7d9a.jpg"},{"id":13571785,"identity":"f5211a69-6ed3-4c5a-acfc-e759014bcb59","added_by":"auto","created_at":"2021-09-17 03:48:51","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2788947,"visible":true,"origin":"","legend":"","description":"","filename":"EPS2020revisedmanuscriptclean.pdf","url":"https://assets-eu.researchsquare.com/files/rs-53570/v2_covered.pdf"},{"id":13522089,"identity":"8940389e-b9aa-4c61-a29e-c19b88535a26","added_by":"auto","created_at":"2021-09-17 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AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"magnetotelluric (MT), refined composite multiscale dispersion entropy (RCMDE), orthogonal matching pursuit (OMP), noise separation","lastPublishedDoi":"10.21203/rs.3.rs-53570/v2","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-53570/v2","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Magnetotelluric (MT) data processing can increase the reliability of measured data. Traditional MT de-noising methods are usually filtered in entire MT time-series sequence, which result in losing of useful MT signals and the decrease of imaging accuracy of electromagnetic inversion. However, targeted MT noise separation can retain the part of data not affected by strong noise, and enhance the quality of MT data. Thus, we proposed a novel method for MT noise separation, which using refined composite multiscale dispersion entropy (RCMDE) and orthogonal matching pursuit (OMP). Firstly, the RCMDE characteristic parameters are extracted from each segment of the MT time-series. Then, the characteristic parameters are input to the fuzzy c-mean (FCM) clustering for automatic identification of MT signal and noise. Next, OMP method is utilized to remove the identified noise segments independently. Finally, the reconstructed signal consists of the denoised data segments and the identified useful signal segments. We conducted the simulation experiments and algorithm evaluation on the EMTF data, simulated data and measured sites. The results indicate that the RCMDE can improve the stability of multiscale dispersion entropy (MDE) and multiscale entropy (MSE) by analyzing the characteristics of the signal samples library, effectively dividing MT signals and noise. Compared with the existing techniques of the entire time domain de-noising and signal-noise identification, the proposed method used RCMDE and OMP as characteristic parameter and noise separation, simplified the multi-features fusion, and improved the accuracy of signal-noise identification. Moreover, the de-noising efficiency has accelerated, and the MT data quality of low-frequency band has improved greatly.","manuscriptTitle":"Separation of magnetotelluric signals based on refined composite multiscale dispersion entropy and orthogonal matching pursuit","msid":"","msnumber":"","nonDraftVersions":[{"code":2,"date":"2021-01-07 18:27:57","doi":"10.21203/rs.3.rs-53570/v2","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major Revision","date":"2021-01-19T00:00:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-01-18T00:00:00+00:00","index":2,"fulltext":"Recommendation: Reviewer's comments unavailable due to the journal's 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