Robust Adaptive Beamforming for Uniform Circular Arrays based on Interference-plus-Noise Covariance Matrix Reconstruction

Robust Adaptive Beamforming for Uniform Circular Arrays based on Interference-plus-Noise Covariance Matrix Reconstruction | 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 Robust Adaptive Beamforming for Uniform Circular Arrays based on Interference-plus-Noise Covariance Matrix Reconstruction Guolin Tian, Weijia Cui, Yuxi Du, Bin Ba, Ruiyu Dou This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6662000/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 practical applications, various model mismatches can significantly degrade the performance of beamformers. In this paper, we propose a robust adaptive beamforming (RAB) algorithm that achieves superior output performance for array models based on the Uniform Circular Array (UCA). The proposed algorithm reconstructs the interference-plus-noise covariance (INC) matrix by estimating the steering vector (SV) of the signal of interest (SOI), interference power, and noise power. Specifically, the eigenvector associated with the SOI is obtained via eigen-decomposition using a subspace algorithm and subsequently employed to estimate the SOI SV. The noise power is estimated by truncated averaging of small eigenvalues obtained through eigen-decomposition. The interference power is then estimated based on the orthogonality property between different signal SVs, facilitating the reconstruction of the INC matrix. Finally, the beamforming weights are calculated using the estimated SOI SV and the reconstructed INC matrix. The proposed algorithm only requires prior knowledge of the UCA geometry and the angular sector that contains the SOI SV. Simulation results are provided to demonstrate that the proposed algorithm effectively mitigates signal self-cancellation at high signal-to-noise ratios (SNR) and achieves significant improvements in output signal-to-interference-plus-noise ratio (SINR) performance under various mismatch conditions. Physical sciences/Engineering Physical sciences/Engineering/Electrical and electronic engineering Robust adaptive beamforming for uniform circle arrays INC matrix reconstruction SV estimation power estimation 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-6662000","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":464685392,"identity":"54911550-b2de-4348-918b-b05bbe81588b","order_by":0,"name":"Guolin Tian","email":"","orcid":"","institution":"PLA Information Engineering University","correspondingAuthor":false,"prefix":"","firstName":"Guolin","middleName":"","lastName":"Tian","suffix":""},{"id":464685393,"identity":"141a1988-8212-440a-9ebd-48f04aa58e94","order_by":1,"name":"Weijia Cui","email":"","orcid":"","institution":"PLA Information Engineering University","correspondingAuthor":false,"prefix":"","firstName":"Weijia","middleName":"","lastName":"Cui","suffix":""},{"id":464685394,"identity":"41d34710-7675-40e1-b3f9-3c812e6d2b79","order_by":2,"name":"Yuxi Du","email":"","orcid":"","institution":"PLA Information Engineering University","correspondingAuthor":false,"prefix":"","firstName":"Yuxi","middleName":"","lastName":"Du","suffix":""},{"id":464685395,"identity":"b7ae2a5b-b341-4a4d-98c3-7e6ad6a460b8","order_by":3,"name":"Bin Ba","email":"","orcid":"","institution":"PLA Information Engineering University","correspondingAuthor":false,"prefix":"","firstName":"Bin","middleName":"","lastName":"Ba","suffix":""},{"id":464685396,"identity":"29b89ac1-f5ff-4b96-9a34-5bc788876a17","order_by":4,"name":"Ruiyu Dou","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAArUlEQVRIiWNgGAWjYDCCA0D8gMGGh5+9gRQtCQxpMpI9B0jTctjG4IYDkTr4bp8xYEhsO8/DcIOB8cPHHCK0SJ7LAWm5zcM4u4FZcuY2IrQYnOGBaGGWOcDGzEuClnM8bBIJpGk5wMNDtBbJM2wFDAnnknkkeA42E+cXvjPMGxg+lNnZ2x9vPvjhIzFaGBg4zH8wsoEYjA1EqQcC9gcMDH+IVTwKRsEoGAUjEgAA7Pk0fOPUJYEAAAAASUVORK5CYII=","orcid":"","institution":"PLA Information Engineering University","correspondingAuthor":true,"prefix":"","firstName":"Ruiyu","middleName":"","lastName":"Dou","suffix":""}],"badges":[],"createdAt":"2025-05-14 08:23:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6662000/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6662000/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86642279,"identity":"b79df7ab-241f-4f1e-95f2-065465c35de2","added_by":"auto","created_at":"2025-07-14 08:24:08","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":646110,"visible":true,"origin":"","legend":"","description":"","filename":"RobustAdaptiveBeamformingforUniformCircularArraysbasedonInterferenceplusNoiseCovarianceMatrixReconstruction.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6662000/v1_covered_211a1df9-123c-493a-aeb8-2a116e7f3871.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Robust Adaptive Beamforming for Uniform Circular Arrays based on Interference-plus-Noise Covariance Matrix Reconstruction","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":"Robust adaptive beamforming for uniform circle arrays, INC matrix reconstruction, SV estimation, power estimation","lastPublishedDoi":"10.21203/rs.3.rs-6662000/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6662000/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"In practical applications, various model mismatches can significantly degrade the performance of beamformers. In this paper, we propose a robust adaptive beamforming (RAB) algorithm that achieves superior output performance for array models based on the Uniform Circular Array (UCA). The proposed algorithm reconstructs the interference-plus-noise covariance (INC) matrix by estimating the steering vector (SV) of the signal of interest (SOI), interference power, and noise power. Specifically, the eigenvector associated with the SOI is obtained via eigen-decomposition using a subspace algorithm and subsequently employed to estimate the SOI SV. The noise power is estimated by truncated averaging of small eigenvalues obtained through eigen-decomposition. The interference power is then estimated based on the orthogonality property between different signal SVs, facilitating the reconstruction of the INC matrix. Finally, the beamforming weights are calculated using the estimated SOI SV and the reconstructed INC matrix. The proposed algorithm only requires prior knowledge of the UCA geometry and the angular sector that contains the SOI SV. Simulation results are provided to demonstrate that the proposed algorithm effectively mitigates signal self-cancellation at high signal-to-noise ratios (SNR) and achieves significant improvements in output signal-to-interference-plus-noise ratio (SINR) performance under various mismatch conditions.","manuscriptTitle":"Robust Adaptive Beamforming for Uniform Circular Arrays based on Interference-plus-Noise Covariance Matrix Reconstruction","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-02 06:10:13","doi":"10.21203/rs.3.rs-6662000/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":"e16985d9-3902-4311-96f1-6498c48df508","owner":[],"postedDate":"June 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":49336819,"name":"Physical sciences/Engineering"},{"id":49336820,"name":"Physical sciences/Engineering/Electrical and electronic engineering"}],"tags":[],"updatedAt":"2025-12-02T05:53:27+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-02 06:10:13","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6662000","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6662000","identity":"rs-6662000","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}