A Radar Vital Signs Detection Method in Complex Environments

A Radar Vital Signs Detection Method in Complex Environments | 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 A Radar Vital Signs Detection Method in Complex Environments Chaoyan Zhang, Hui Liu, Yi Zhu, Guangjie Fu, Xianzhen Chen, Daixin Yang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6485609/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 19 Jan, 2026 Read the published version in Scientific Reports → Version 1 posted 11 You are reading this latest preprint version Abstract With the growing demand for non-contact monitoring of vital signs such as respiration and heartbeat, frequency-modulatedcontinuous wave (FMCW) radars have emerged as a promising solution for precise analysis of these signals. However, incomplex environments such as indoors or inside vehicles, masking effects significantly degrade the accuracy of the target’sdistance. Additionally multiple harmonics of the respiration frequency can easily leak into the heartbeat frequency range,resulting in biased heart rate estimation. To address these challenges, we propose the Matrix Coefficient Selection Method(MCSM), a robust distance detection approach that suppresses interference between targets and mitigate the impact of otherobstacles in the environment, thereby improving the robustness of distance detection, particularly in multi-target scenarios.Inspired by the harmonic mitigation techniques employed in power systems, we propose RLSRHS, which is derived froman improved adaptive filter structure, to suppress respiratory harmonics. Simulation experiments demonstrate that theMCSM method reduces the MAE by approximately 40% at distance detection compared to traditional methods, while theRLSRHS method effectively suppresses interference from respiratory harmonics. Extensive real-world experiments, includingcomparisons with ECG monitoring devices, bracelets, and breath sensors, further validate the simulation results, with the errorin heart rate and respiration rate being approximately 4%. Health sciences/Health care Physical sciences/Engineering Physical sciences/Mathematics and computing Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 19 Jan, 2026 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 07 Oct, 2025 Reviews received at journal 28 Sep, 2025 Reviewers agreed at journal 18 Sep, 2025 Reviews received at journal 27 Jul, 2025 Reviewers agreed at journal 10 Jul, 2025 Reviewers agreed at journal 10 Jul, 2025 Reviewers invited by journal 10 Jul, 2025 Editor assigned by journal 30 Apr, 2025 Editor invited by journal 30 Apr, 2025 Submission checks completed at journal 28 Apr, 2025 First submitted to journal 19 Apr, 2025 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-6485609","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":483787185,"identity":"e199475a-2a29-4e38-974d-dd23457aa63e","order_by":0,"name":"Chaoyan Zhang","email":"","orcid":"","institution":"Xiamen University","correspondingAuthor":false,"prefix":"","firstName":"Chaoyan","middleName":"","lastName":"Zhang","suffix":""},{"id":483787186,"identity":"aa39a5dd-45f7-4013-9a57-eace926c750e","order_by":1,"name":"Hui Liu","email":"","orcid":"","institution":"Xiamen University","correspondingAuthor":false,"prefix":"","firstName":"Hui","middleName":"","lastName":"Liu","suffix":""},{"id":483787187,"identity":"0570627b-0295-4712-8385-2cea3319e55b","order_by":2,"name":"Yi Zhu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAsklEQVRIiWNgGAWjYDACCSBOqECwidVyhmQtjG2kaJGf3WMm8XDe4WiDA8wHb/Mw2OUR1MI454yZROK2tNwNB9iSrXkYkosJamGWyAFpsQFq4TGT5mE4kNhASAsbWMscCaAW/m/EaeEBa2kA28JGnBYJibRii4RjabkzD7MZW84xSCasRX5G8sabP2oO5/Ydb354402FHWEtQMACiQ5mEGFAhHqQ2g/EqRsFo2AUjIIRCwBNpjc55f4X1gAAAABJRU5ErkJggg==","orcid":"","institution":"Xiamen University","correspondingAuthor":true,"prefix":"","firstName":"Yi","middleName":"","lastName":"Zhu","suffix":""},{"id":483787188,"identity":"c95eaa20-b075-41e9-a128-66c9d5ddbca9","order_by":3,"name":"Guangjie Fu","email":"","orcid":"","institution":"Xiamen University","correspondingAuthor":false,"prefix":"","firstName":"Guangjie","middleName":"","lastName":"Fu","suffix":""},{"id":483787189,"identity":"62940aef-bafa-4112-add3-7bb7cc058ed1","order_by":4,"name":"Xianzhen Chen","email":"","orcid":"","institution":"Xiamen University","correspondingAuthor":false,"prefix":"","firstName":"Xianzhen","middleName":"","lastName":"Chen","suffix":""},{"id":483787190,"identity":"6e84f046-0cb0-432c-953a-df2f54f3638a","order_by":5,"name":"Daixin Yang","email":"","orcid":"","institution":"Xiamen University","correspondingAuthor":false,"prefix":"","firstName":"Daixin","middleName":"","lastName":"Yang","suffix":""}],"badges":[],"createdAt":"2025-04-19 15:38:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6485609/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6485609/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-32042-6","type":"published","date":"2026-01-19T15:57:21+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":101153344,"identity":"b4ed5f35-4e03-4f2a-80d8-33be22ae2708","added_by":"auto","created_at":"2026-01-26 16:14:49","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6859154,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscriptfile.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6485609/v1_covered_167787a9-8f3d-464c-9ccf-28b01f726f30.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Radar Vital Signs Detection Method in Complex Environments","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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6485609/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6485609/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"With the growing demand for non-contact monitoring of vital signs such as respiration and heartbeat, frequency-modulatedcontinuous wave (FMCW) radars have emerged as a promising solution for precise analysis of these signals. However, incomplex environments such as indoors or inside vehicles, masking effects significantly degrade the accuracy of the target’sdistance. Additionally multiple harmonics of the respiration frequency can easily leak into the heartbeat frequency range,resulting in biased heart rate estimation. To address these challenges, we propose the Matrix Coefficient Selection Method(MCSM), a robust distance detection approach that suppresses interference between targets and mitigate the impact of otherobstacles in the environment, thereby improving the robustness of distance detection, particularly in multi-target scenarios.Inspired by the harmonic mitigation techniques employed in power systems, we propose RLSRHS, which is derived froman improved adaptive filter structure, to suppress respiratory harmonics. 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