Wavelet Denoising of Inertial Sensor Input Data for Gnss-ins Integration: Simulation Approach

Wavelet Denoising of Inertial Sensor Input Data for Gnss-ins Integration: Simulation Approach | 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 Article Wavelet Denoising of Inertial Sensor Input Data for Gnss-ins Integration: Simulation Approach Karamtot Krishna Naik This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7327936/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract The Global Navigation Satellite Systems (GNSS) provides autonomous geospatial positioning across the globe, in the name of GPS, GLONASS, GALILEO, Beiduo, and other regional systems like IRNSS, QZSS. The advantage of having access to multiple satellites is accuracy, redundancy, and availability at all times. GPS (Global Positioning System) was the first GNSS in the United States which offers excellent multi-constellation solutions consists of up to 32 medium Earth observation satellites in six different orbital planes of four satellites in each can be used for many purposes like commercial, military, space, agriculture and so many. The Inertial Navigation System (INS) is a self-dependent system that does not depend on external electronic signals. Using the basic laws proposed by Issac Newton, it gives the position based on the time distance relation. The basic need of this navigation system is to know the initial position and the time at which the vehicle starts navigation. It mainly consists of two devices namely accelerometers and gyroscopes which give the amount of acceleration and rotational information of the moving vehicle using inertial sensors. GPS signal is an electromagnetic signal, can be blocked by mountains, dense forests, areas with high buildings, and in bad weather conditions. Therefore, GPS is not continuous all the time where INS is in any situation. Because of this drawback integration of GPS and INS is needed to provide continuous information all the time. The INS will update the GPS measurements whenever it is required and it will also correct GPS phase cycle slips. But most of the errors in the INS are caused by sensor short-term errors that have to be rectified before giving it as an input to the IMU for integration. The wavelet signal processing technique is applied to improve navigation signals. The wavelet will decompose the signal to multiple levels to improve the performance of the inertial sensor signals by separating the signal into lower and higher frequency noise components. However, the wavelet threshold method does not distort the rapidly-changing signal but reduces signal noise. This paper has applied different threshold techniques as part of simulation to improve the navigational performance of the experiment. On performing the wavelet denoising decimated wavelet transform and un-decimated wavelet transform using level-dependent soft threshold technique and also the hybrid un- decimated transform with the least square method as threshold technique results in the reduction of noise. Physical sciences/Engineering Physical sciences/Mathematics and computing Physical sciences/Physics GNSS INS Integration Wavelet transform De Noising Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editor invited by journal 08 May, 2026 Reviews received at journal 16 Apr, 2026 Reviews received at journal 14 Apr, 2026 Reviewers agreed at journal 26 Mar, 2026 Reviewers agreed at journal 25 Mar, 2026 Reviewers agreed at journal 24 Mar, 2026 Reviewers agreed at journal 17 Sep, 2025 Reviewers agreed at journal 14 Sep, 2025 Reviewers invited by journal 12 Sep, 2025 Editor assigned by journal 04 Sep, 2025 Submission checks completed at journal 01 Sep, 2025 First submitted to journal 01 Sep, 2025 You are reading this latest preprint version 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-7327936","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":516800686,"identity":"d22729f9-c640-4bae-b09a-7ac9ef184ca9","order_by":0,"name":"Karamtot Krishna 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Approach\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"GNSS, INS, Integration, Wavelet transform, De Noising","lastPublishedDoi":"10.21203/rs.3.rs-7327936/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7327936/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The Global Navigation Satellite Systems (GNSS) provides autonomous geospatial positioning across the globe, in the name of GPS, GLONASS, GALILEO, Beiduo, and other regional systems like IRNSS, QZSS. The advantage of having access to multiple satellites is accuracy, redundancy, and availability at all times. GPS (Global Positioning System) was the first GNSS in the United States which offers excellent multi-constellation solutions consists of up to 32 medium Earth observation satellites in six different orbital planes of four satellites in each can be used for many purposes like commercial, military, space, agriculture and so many. The Inertial Navigation System (INS) is a self-dependent system that does not depend on external electronic signals. Using the basic laws proposed by Issac Newton, it gives the position based on the time distance relation. The basic need of this navigation system is to know the initial position and the time at which the vehicle starts navigation. It mainly consists of two devices namely accelerometers and gyroscopes which give the amount of acceleration and rotational information of the moving vehicle using inertial sensors. GPS signal is an electromagnetic signal, can be blocked by mountains, dense forests, areas with high buildings, and in bad weather conditions. Therefore, GPS is not continuous all the time where INS is in any situation. Because of this drawback integration of GPS and INS is needed to provide continuous information all the time. The INS will update the GPS measurements whenever it is required and it will also correct GPS phase cycle slips. But most of the errors in the INS are caused by sensor short-term errors that have to be rectified before giving it as an input to the IMU for integration. The wavelet signal processing technique is applied to improve navigation signals. The wavelet will decompose the signal to multiple levels to improve the performance of the inertial sensor signals by separating the signal into lower and higher frequency noise components. However, the wavelet threshold method does not distort the rapidly-changing signal but reduces signal noise. This paper has applied different threshold techniques as part of simulation to improve the navigational performance of the experiment. On performing the wavelet denoising decimated wavelet transform and un-decimated wavelet transform using level-dependent soft threshold technique and also the hybrid un- decimated transform with the least square method as threshold technique results in the reduction of noise.","manuscriptTitle":"Wavelet Denoising of Inertial Sensor Input Data for Gnss-ins Integration: Simulation Approach","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-22 04:15:05","doi":"10.21203/rs.3.rs-7327936/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvited","content":"","date":"2026-05-08T13:21:44+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-16T05:43:18+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-14T09:46:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"23804601556921143975861546025658222025","date":"2026-03-27T02:24:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"106015598779787803275595561673981506875","date":"2026-03-25T05:10:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"188279937322837460187692372645115205433","date":"2026-03-24T12:48:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"213816403229642104783931231806843860857","date":"2025-09-17T09:42:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"170502885883325887744338180739993105897","date":"2025-09-15T02:03:55+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-13T02:00:06+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-04T20:24:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-01T05:30:51+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-09-01T05:26:11+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"18ea4ad5-eda7-4766-978a-3a91734bf07b","owner":[],"postedDate":"September 22nd, 2025","published":true,"recentEditorialEvents":[{"type":"editorInvited","content":"","date":"2026-05-08T13:21:44+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":55086137,"name":"Physical sciences/Engineering"},{"id":55086138,"name":"Physical sciences/Mathematics and computing"},{"id":55086139,"name":"Physical sciences/Physics"}],"tags":[],"updatedAt":"2025-09-22T04:15:06+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-22 04:15:05","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7327936","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7327936","identity":"rs-7327936","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}