·Assessment of Unmanned Aerial Vehicle Cluster Detection and Perception Capability

·Assessment of Unmanned Aerial Vehicle Cluster Detection and Perception Capability | 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 ·Assessment of Unmanned Aerial Vehicle Cluster Detection and Perception Capability Beibei ZHAO, Yu Chen, Xiaogang Qi, Lifang LIU This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4309110/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 For the evaluation of unmanned aerial vehicle (UAV) cluster detection and perception capability, a model for assessing the UAV cluster detection and perception capability is established based on the reconnaissance mission of the swarm. An evaluation method based on the three-parameter interval number weighted Hamy mean operator, analytic hierarchy process (AHP), and entropy weight method is proposed. Firstly, an evaluation matrix is established at multiple moments. Secondly, the evaluation matrices of multiple moments are aggregated through the inverse form of the Poisson distribution. Then, the weights of the indicators are calculated using the combination weighting method. Finally, the three-parameter interval number weighted Hamy mean operator is used to aggregate the evaluation indicator information. Simulation results show that the proposed evaluation method can effectively handle the uncertainty of information and is suitable for complex combat environments, providing quantitative references for decision-making related to UAV swarm operations. UAV Detection sensing capability three-parameter interval number Hamy mean operator 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. 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-4309110","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":298821188,"identity":"8ce764f0-48b3-4d76-a656-577635ed9990","order_by":0,"name":"Beibei ZHAO","email":"","orcid":"","institution":"Xidian University","correspondingAuthor":false,"prefix":"","firstName":"Beibei","middleName":"","lastName":"ZHAO","suffix":""},{"id":298821190,"identity":"e35ed85f-37b3-454c-9e77-08d404839c0d","order_by":1,"name":"Yu Chen","email":"","orcid":"","institution":"Science and Technology on Near-Surface Detection Laboratory","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Chen","suffix":""},{"id":298821192,"identity":"b79d1cb0-f9f2-498e-a564-be2ec778abca","order_by":2,"name":"Xiaogang Qi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYDACZjiD+QCQPECSFrYEqBZmXGoxAI8BcVoMjjM/fPil5o5d33GebxIfau4wmLP343edZDObsbHMsWfJMw/zbpOccewZg2XPYfy28DMzmElLsB1ONgBqkeZhO8xgcCMZvxY2ZvZv0hL/QFp4nkn/+QfUcv8xIVt4zCQ/th22A2phk2ZsA9lCwPuSzTzFxox9hxMkD7MZW/b2HeYxOJNsgFeLwfnjGx/++HbYnu/84Yc3gAw5g+MHH+C3BgiYeRgYEhsOMLBIADk8BJWDAOMPBgZ7YCQyfyBK+SgYBaNgFIw4AAAiQEopMkIYNQAAAABJRU5ErkJggg==","orcid":"","institution":"Xidian University","correspondingAuthor":true,"prefix":"","firstName":"Xiaogang","middleName":"","lastName":"Qi","suffix":""},{"id":298821195,"identity":"9a78c524-0c23-434f-87f8-3d5881343793","order_by":3,"name":"Lifang LIU","email":"","orcid":"","institution":"Xidian University","correspondingAuthor":false,"prefix":"","firstName":"Lifang","middleName":"","lastName":"LIU","suffix":""}],"badges":[],"createdAt":"2024-04-23 03:55:44","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4309110/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4309110/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":57093970,"identity":"41769b73-e23c-4ff8-8f5a-c8d2ea4c14b7","added_by":"auto","created_at":"2024-05-24 13:44:33","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":297267,"visible":true,"origin":"","legend":"","description":"","filename":"paper.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4309110/v1_covered_de655b7b-29ce-42f4-b461-f53d5d63d44d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"·Assessment of Unmanned Aerial Vehicle Cluster Detection and Perception Capability","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":"UAV, Detection sensing capability, three-parameter interval number, Hamy mean operator","lastPublishedDoi":"10.21203/rs.3.rs-4309110/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4309110/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eFor the evaluation of unmanned aerial vehicle (UAV) cluster detection and perception capability, a model for assessing the UAV cluster detection and perception capability is established based on the reconnaissance mission of the swarm. An evaluation method based on the three-parameter interval number weighted Hamy mean operator, analytic hierarchy process (AHP), and entropy weight method is proposed. Firstly, an evaluation matrix is established at multiple moments. Secondly, the evaluation matrices of multiple moments are aggregated through the inverse form of the Poisson distribution. Then, the weights of the indicators are calculated using the combination weighting method. Finally, the three-parameter interval number weighted Hamy mean operator is used to aggregate the evaluation indicator information. 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