OFDM Source Localization Algorithm for Multiple Arrays in Multipath Environments via Combining Enhanced Spatial Smoothing and Clustering

OFDM Source Localization Algorithm for Multiple Arrays in Multipath Environments via Combining Enhanced Spatial Smoothing and Clustering | 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 OFDM Source Localization Algorithm for Multiple Arrays in Multipath Environments via Combining Enhanced Spatial Smoothing and Clustering Shenghui Zhao, Heng Yue, Bingzhi Shi, Xiaofei Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7276559/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 Mar, 2026 Read the published version in Wireless Personal Communications → Version 1 posted 11 You are reading this latest preprint version Abstract When addressing the problem of signal source localization in multipath environments, traditional subspace‑based algorithms often suffer from rank deficiency. This issue severely degrades the performance of angle-of-arrival (AOA) estimation. This paper focuses on the localization of orthogonal frequency division multiplexing (OFDM) sources in multipath environments. A low-complexity two-step localization method based on spatial smoothing is put forward. First, enhanced spatial smoothing preprocessing on the signal subspace (ESSP-SS) is performed to overcome the covariance matrix's rank deficiency. Next, the accurate estimation of AOAs is realized by using the multi-carrier property. Then, the line-of-sight (LOS) is identified by exploiting the power differences between LOS and non-line-of-sight (NLOS) paths. Finally, the clustering algorithm fuses LOS angle estimates from multiple antenna arrays to determine the source position. The simulation outcomes indicate that the proposed method significantly improves positioning precision in multipath scenarios. angle-of-arrival orthogonal frequency division multiplexing enhanced spatial smoothing clustering Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 09 Mar, 2026 Read the published version in Wireless Personal Communications → Version 1 posted Editorial decision: Revision requested 13 Oct, 2025 Reviews received at journal 07 Oct, 2025 Reviews received at journal 30 Sep, 2025 Reviews received at journal 20 Sep, 2025 Reviewers agreed at journal 20 Sep, 2025 Reviewers agreed at journal 18 Sep, 2025 Reviewers agreed at journal 14 Sep, 2025 Reviewers invited by journal 14 Sep, 2025 Editor assigned by journal 07 Aug, 2025 Submission checks completed at journal 07 Aug, 2025 First submitted to journal 02 Aug, 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-7276559","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":518015365,"identity":"9da86142-8301-4310-934a-5ea566ca2e88","order_by":0,"name":"Shenghui 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