Accounting for Observation Data Quality in Station Selection for UPD Estimation

Accounting for Observation Data Quality in Station Selection for UPD Estimation | 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 Accounting for Observation Data Quality in Station Selection for UPD Estimation Shouzhou Gu, Long Xiao, Jinzhong Mi, Xuan Zhao, Yidong Fan, Bin Chu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8806795/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 13 You are reading this latest preprint version Abstract Targeting the issues of uneven spatial distribution and significant variations in observation data quality among Multi-GNSS Experiment (MGEX) stations, this paper proposes an adaptive station selection method for Uncalibrated Phase Delay (UPD) estimation that incorporates observation data quality, overcoming the limitations of traditional methods which often overlook station geometry and data quality. A Position Dilution of Precision (PDOP) and UPD error propagation model is developed. Using marginal benefit theory, the optimal number of stations is determined. A multi-indicator evaluation system based on Dempster-Shafer (D-S) evidence theory is established to assess data quality, enabling a dynamic grid algorithm that balances spatial geometry and data quality. Experimental results demonstrate that the proposed method selects 80 optimal stations, accounting for only 30% of the global stations. The estimated narrow-lane UPD products achieve an accuracy better than 0.05 cycles, with a discrepancy of less than 0.002 cycles compared to the full-station solution, indicating comparable precision. Furthermore, the computational time is reduced by 54.1%. Physical sciences/Engineering Physical sciences/Mathematics and computing adaptive station selection Dempster-Shafer (D-S) evidence theory dynamic grid marginal benefit observation data quality Position Dilution of Precision (PDOP) Uncalibrated Phase Delay (UPD) Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 08 Apr, 2026 Reviews received at journal 06 Apr, 2026 Reviews received at journal 29 Mar, 2026 Reviews received at journal 23 Mar, 2026 Reviewers agreed at journal 19 Mar, 2026 Reviewers agreed at journal 19 Mar, 2026 Reviewers agreed at journal 17 Mar, 2026 Reviewers agreed at journal 17 Mar, 2026 Reviewers invited by journal 17 Mar, 2026 Editor assigned by journal 12 Mar, 2026 Editor invited by journal 16 Feb, 2026 Submission checks completed at journal 13 Feb, 2026 First submitted to journal 13 Feb, 2026 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. 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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-8806795","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":608944124,"identity":"a70efb89-83e6-4185-a1e8-798001561450","order_by":0,"name":"Shouzhou Gu","email":"","orcid":"","institution":"Chinese Academy of Surveying and Mapping","correspondingAuthor":false,"prefix":"","firstName":"Shouzhou","middleName":"","lastName":"Gu","suffix":""},{"id":608944125,"identity":"6c5fd049-ffeb-442b-be34-7368b66df6af","order_by":1,"name":"Long 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