A Digital Twin-Driven Computation and Analysis Framework for Low-Altitude Airspace

A Digital Twin-Driven Computation and Analysis Framework for Low-Altitude Airspace | 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 A Digital Twin-Driven Computation and Analysis Framework for Low-Altitude Airspace Zhenghan HE, Weibin ZHANG, Peng DU, Zhiyong LIU This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8500641/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 To address key challenges in low-altitude airspace management, such as high dynamic complexity, significant safety risks, and information fragmentation, a digital twin-based methodology for low-altitude airspace computation and analysis is proposed in this paper. First, a four-layer digital twin system architecture is established. High-fidelity digital twin mapping of the low-altitude airspace is achieved through the integration of multi-source heterogeneous data, the application of unified spatio-temporal representation, the implementation of dynamic evolution modeling, and the facilitation of bidirectional physical-virtual closed-loop interaction. Second, innovative intelligent algorithms, including a bidirectional GRU-Seq2Seq trajectory prediction model and a Kalman filter-based error compensation mechanism, are incorporated. These components form a comprehensive technical framework that supports quantitative airspace resource evaluation, real-time trajectory analysis, and conflict prediction and early warning. Finally, experimental validation is conducted across three scenarios: single-target conventional flight, multi-target collaborative flight, and extreme weather interference. The results indicate that, compared with the conventional geometric twin approach, the proposed method achieves a 37.2% reduction in trajectory deviation, a 62.5% improvement in conflict warning accuracy, and a 28.6% enhancement in site selection safety. Furthermore, it is shown to outperform traditional methods across five core performance metrics, including computational efficiency and trajectory accuracy, which further confirms its strong suitability for supporting the high-quality development of the low-altitude economy. digital twin low-altitude airspace computational analysis intelligent site selection conflict early warning trajectory analysis Full Text Additional Declarations No competing interests reported. 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. 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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-8500641","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":583554703,"identity":"4a1bd78f-537a-4838-ac87-1e8f7c64240e","order_by":0,"name":"Zhenghan HE","email":"","orcid":"","institution":"Xian Yang Polytechnic Institute","correspondingAuthor":false,"prefix":"","firstName":"Zhenghan","middleName":"","lastName":"HE","suffix":""},{"id":583554704,"identity":"545ba640-c603-4e1f-914d-95252985ec10","order_by":1,"name":"Weibin ZHANG","email":"","orcid":"","institution":"Xian Yang Polytechnic Institute","correspondingAuthor":false,"prefix":"","firstName":"Weibin","middleName":"","lastName":"ZHANG","suffix":""},{"id":583554705,"identity":"c2557dae-c731-418f-8a56-e09b0d0d3261","order_by":2,"name":"Peng DU","email":"","orcid":"","institution":"Xian Yang Polytechnic Institute","correspondingAuthor":false,"prefix":"","firstName":"Peng","middleName":"","lastName":"DU","suffix":""},{"id":583554706,"identity":"9a4d7c72-6647-4d2e-8010-23908cd12242","order_by":3,"name":"Zhiyong LIU","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAv0lEQVRIiWNgGAWjYFAC5gYDICnHxt5+gFgtjGAtxnw8ZxKI1wIiE+dJOBgQp8Hg+MGGYp4/h9PbJBgSGH5UbCNCy5nEBsMZPIdz26QbDzD2nLlNWIvZgcQGgw8SQC0yBxKYGduI0XL+YYNBgsHhdDaJBAMitdwA2ZJwOIF4LfY3HgL9ciDdsA0YyAeJ8otkf/IxY54/1vLy7e0HH/yoIEILELAB46MZzDpAlHogYH7AwFBHrOJRMApGwSgYiQAALO0/Y/bKbBAAAAAASUVORK5CYII=","orcid":"","institution":"Xian Yang Polytechnic Institute","correspondingAuthor":true,"prefix":"","firstName":"Zhiyong","middleName":"","lastName":"LIU","suffix":""}],"badges":[],"createdAt":"2026-01-02 11:53:49","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8500641/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8500641/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103369363,"identity":"4dff025c-1b53-4254-8ad5-a20e01999986","added_by":"auto","created_at":"2026-02-25 01:24:51","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":636462,"visible":true,"origin":"","legend":"","description":"","filename":"ADigitalTwinDrivenFrameworkforCalculatingandAnalyzingLowAltitudeAirspaceUtilization.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8500641/v1_covered_89c96884-8c67-4301-af3e-639c23cca888.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Digital Twin-Driven Computation and Analysis Framework for Low-Altitude Airspace","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":"digital twin, low-altitude airspace, computational analysis, intelligent site selection, conflict early warning, trajectory analysis","lastPublishedDoi":"10.21203/rs.3.rs-8500641/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8500641/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTo address key challenges in low-altitude airspace management, such as high dynamic complexity, significant safety risks, and information fragmentation, a digital twin-based methodology for low-altitude airspace computation and analysis is proposed in this paper. First, a four-layer digital twin system architecture is established. High-fidelity digital twin mapping of the low-altitude airspace is achieved through the integration of multi-source heterogeneous data, the application of unified spatio-temporal representation, the implementation of dynamic evolution modeling, and the facilitation of bidirectional physical-virtual closed-loop interaction. Second, innovative intelligent algorithms, including a bidirectional GRU-Seq2Seq trajectory prediction model and a Kalman filter-based error compensation mechanism, are incorporated. These components form a comprehensive technical framework that supports quantitative airspace resource evaluation, real-time trajectory analysis, and conflict prediction and early warning. Finally, experimental validation is conducted across three scenarios: single-target conventional flight, multi-target collaborative flight, and extreme weather interference. 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