A multi-fidelity transfer learning strategy for surface deformation measurement of large reflector antennas

A multi-fidelity transfer learning strategy for surface deformation measurement of large reflector antennas | 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 multi-fidelity transfer learning strategy for surface deformation measurement of large reflector antennas Zihan Zhang, Qian Ye, Na Wang, Guoxiang Meng This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4950117/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Feb, 2025 Read the published version in Experimental Astronomy → Version 1 posted 9 You are reading this latest preprint version Abstract As the observation frequency of large-aperture antennas increases, the requirements for measuring main reflector deformation have become more stringent. Recently, the rapid development of deep learning has led to its application in antenna deformation prediction. However, achieving high accuracy requires a large number of high-fidelity deformation samples, which is often challenging to obtain. To address these problems, this paper establishes a high-accuracy antenna surface deformation measurement model based on a multi-fidelity transfer learning neural network (MF-TLNN). Firstly, a low-fidelity surrogate model is constructed using a large number of simulation deformation samples to ensure its robustness. Secondly, the MF-TLNN structure is designed and trained using a small number of high-fidelity samples obtained from actual measurements of the main reflector deformation. Thirdly, a Zernike correction module is utilized to provide additional constraints and ensure the stability of the results. Experimental results show that the proposed method can closely approximate radio holography measurements in terms of accuracy and is almost real-time in terms of speed. Large-aperture reflector antenna Surface deformation measurement Multi-fidelity surrogate model Transfer learning Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 06 Feb, 2025 Read the published version in Experimental Astronomy → Version 1 posted Editorial decision: Revision requested 18 Dec, 2024 Reviews received at journal 03 Dec, 2024 Reviews received at journal 22 Nov, 2024 Reviewers agreed at journal 04 Nov, 2024 Reviewers agreed at journal 29 Oct, 2024 Reviewers invited by journal 07 Oct, 2024 Editor assigned by journal 27 Aug, 2024 Submission checks completed at journal 25 Aug, 2024 First submitted to journal 21 Aug, 2024 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-4950117","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":349387854,"identity":"eedaec64-0271-4763-b3c3-6b40f6cf570f","order_by":0,"name":"Zihan Zhang","email":"","orcid":"","institution":"Shanghai Jiao Tong University","correspondingAuthor":false,"prefix":"","firstName":"Zihan","middleName":"","lastName":"Zhang","suffix":""},{"id":349387855,"identity":"f9b8f90e-9853-497d-b89f-65e9c38337b7","order_by":1,"name":"Qian Ye","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxUlEQVRIiWNgGAWjYJCCAwwMNgwGpGpJI1ELEBwmQYvB8eaNB37uOG9vzn74AMOPGgZ5c4JazhwrONh75nbizp60BMaeYwyGOxsIabmRY3CAt+12gsGBHAMG3gYGIIOQlvtvDA7+bTtnb3D+jQHjX6K03OAxOMzbdoBxA9A6ZqJskTyTVnBYti05ccONZwmHZY5JGG4gpIXv+OHNH9+22QEdlnzw4ZsaG3mCtigcQIoRoGIJAuqBQL6B9HgfBaNgFIyCkQYAPbtIBTL0NgwAAAAASUVORK5CYII=","orcid":"","institution":"Shanghai Astronomical Observatory","correspondingAuthor":true,"prefix":"","firstName":"Qian","middleName":"","lastName":"Ye","suffix":""},{"id":349387858,"identity":"5093f479-2a9a-4cb3-aabc-3db0cae006c6","order_by":2,"name":"Na Wang","email":"","orcid":"","institution":"Xinjiang Astronomical Observatory","correspondingAuthor":false,"prefix":"","firstName":"Na","middleName":"","lastName":"Wang","suffix":""},{"id":349387859,"identity":"0356cd05-7d83-4f32-a259-4a3e722adc70","order_by":3,"name":"Guoxiang Meng","email":"","orcid":"","institution":"Shanghai Jiao Tong University","correspondingAuthor":false,"prefix":"","firstName":"Guoxiang","middleName":"","lastName":"Meng","suffix":""}],"badges":[],"createdAt":"2024-08-21 08:52:56","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4950117/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4950117/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10686-025-09980-0","type":"published","date":"2025-02-06T15:57:14+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":75931491,"identity":"726e3a15-82c0-4183-8189-7d79ea712098","added_by":"auto","created_at":"2025-02-10 16:14:56","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":8248814,"visible":true,"origin":"","legend":"","description":"","filename":"MFTLNNantennaExperimentalAstronomy.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4950117/v1_covered_a5740d2c-6ec0-4dd7-9ea6-5186565ec514.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A multi-fidelity transfer learning strategy for surface deformation measurement of large reflector antennas","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"experimental-astronomy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"expa","sideBox":"Learn more about [Experimental Astronomy](http://link.springer.com/journal/10686)","snPcode":"10686","submissionUrl":"https://submission.nature.com/new-submission/10686/3","title":"Experimental Astronomy","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Large-aperture reflector antenna, Surface deformation measurement, Multi-fidelity surrogate model, Transfer learning","lastPublishedDoi":"10.21203/rs.3.rs-4950117/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4950117/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"As the observation frequency of large-aperture antennas increases, the requirements for measuring main reflector deformation have become more stringent. 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