Low complexity pseudorange deviation reduction method based on digital channel characteristic compensation | 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 Research Article Low complexity pseudorange deviation reduction method based on digital channel characteristic compensation Yamu Xiao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6480720/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In this paper, we propose a low complexity digital channel characteristic compensation method for reducing pseudorange deviation caused by group delay generated by non-ideal channels in receivers. The proposed method is based on a general analysis model of group delay using Fourier series decomposition. The channel group delay is decomposed into a series of cascaded trigonometric group delays, and the compensation effect of filters of different orders on group delay is tested through experiments. The analysis results show that compared with the traditional infinite order based all pass filter, only a 5th order filter is needed to compensate for group delay fluctuations up to 150ns. The filter order is much lower than that of traditional group delay calibration filters, and the compensated pseudorange deviation is less than 0.1m. Pseudorange deviation Group latency Fourier series Low complexity Full Text Cite Share Download PDF Status: Posted Version 1 posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-6480720","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":456706446,"identity":"13a784f2-7336-4f1c-ba2d-b8dfceca893b","order_by":0,"name":"Yamu Xiao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAu0lEQVRIiWNgGAWjYLCCDxU2cmzs7QeIU83DwMDYOONMmjEfz5kE4rU087YcTpwn4WBAnBZ7/jXmj3kbmNPbJBgSGH5UbCPCFok3ho1zd7Dltkk3HmDsOXObGC1nDBvenuHJbZM5kMDM2EasFt42iXQ2iQQDIrXw9xg28rYZJJCg5QZb4cwZZxIM24CBfJAov7D3H97w4UPFf3n59vaDD35UEKGFQSIBwT5AhHog4CdS3SgYBaNgFIxgAABSdD2ry+wuBQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0008-3333-4548","institution":"National University of Defense Technology","correspondingAuthor":true,"prefix":"","firstName":"Yamu","middleName":"","lastName":"Xiao","suffix":""}],"badges":[],"createdAt":"2025-04-18 17:41:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6480720/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6480720/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84647750,"identity":"f3a1372a-d32b-49a7-a19b-005aa4057313","added_by":"auto","created_at":"2025-06-15 18:41:53","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1536442,"visible":true,"origin":"","legend":"","description":"","filename":"QT2411224LowcomplexitypseudorangedeviationEURASIP.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6480720/v1_covered_077548d8-f3ac-4c03-a8a0-16fa603705ff.pdf"}],"financialInterests":"","formattedTitle":"Low complexity pseudorange deviation reduction method based on digital channel characteristic compensation","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Pseudorange deviation, Group latency, Fourier series, Low complexity","lastPublishedDoi":"10.21203/rs.3.rs-6480720/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6480720/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn this paper, we propose a low complexity digital channel characteristic compensation method for reducing pseudorange deviation caused by group delay generated by non-ideal channels in receivers. The proposed method is based on a general analysis model of group delay using Fourier series decomposition. The channel group delay is decomposed into a series of cascaded trigonometric group delays, and the compensation effect of filters of different orders on group delay is tested through experiments. The analysis results show that compared with the traditional infinite order based all pass filter, only a 5th order filter is needed to compensate for group delay fluctuations up to 150ns. The filter order is much lower than that of traditional group delay calibration filters, and the compensated pseudorange deviation is less than 0.1m.\u003c/p\u003e","manuscriptTitle":"Low complexity pseudorange deviation reduction method based on digital channel characteristic compensation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-20 04:27:09","doi":"10.21203/rs.3.rs-6480720/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"
[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9cf4c148-7b41-4a49-9e5f-b3a15c2fd0e9","owner":[],"postedDate":"May 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-15T18:33:47+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-20 04:27:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6480720","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6480720","identity":"rs-6480720","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}
Text is read by the "Ask this paper" AI Q&A widget below.
Extraction quality varies by source — PMC NXML preserves structure
cleanly, OA-HTML may include some navigation residue, and OA-PDF can
have broken hyphenation. The publisher copy
(via DOI)
is the canonical version.