Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/117263
DC FieldValueLanguage
dc.contributorDepartment of Land Surveying and Geo-Informatics-
dc.creatorWu, Y-
dc.creatorHe, M-
dc.creatorLi, W-
dc.creatorJian, IY-
dc.creatorYu, Y-
dc.creatorChen, L-
dc.creatorChen, R-
dc.date.accessioned2026-02-09T03:52:55Z-
dc.date.available2026-02-09T03:52:55Z-
dc.identifier.issn1566-2535-
dc.identifier.urihttp://hdl.handle.net/10397/117263-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectiLBSsen_US
dc.subjectIndoor positioningen_US
dc.subjectInternet of Thingsen_US
dc.subjectSmart cityen_US
dc.subjectWi-Fi fine time measurementen_US
dc.titleWi-Fi fine time measurement–principles, applications, and future trends : a surveyen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume118-
dc.identifier.doi10.1016/j.inffus.2025.102992-
dcterms.abstractIEEE 802.11–2016 proposed the Wi-Fi Fine Time Measurement (FTM) protocol, aiming at providing meter or sub-meter level ranging function between smart terminals and Wi-Fi access points (APs). Compared with other indoor positioning technologies for instance, Bluetooth, acoustic, visible light, Ultra-wideband, etc., Wi-Fi has been characterized by low cost, no deployment, and potentially high positioning precision, especially with the enhancement of FTM, which enables Wi-Fi to be a competitive technology for Internet of Things, indoor location-based services (iLBSs), smart city, and many other fields. In this article, we first present a comprehensive survey that focuses on the Wi-Fi FTM technology, which contains the working principle, measurement for positioning, and methods comparison. We highlight the current FTM-related localization methods especially learning and multi-source fusion-based approaches. Then, we review the real-world applications and existing commercial solutions, revealing the possible directions for the industrialization of Wi-Fi FTM localization. Finally, this paper analyzes existing open issues of Wi-Fi FTM positioning (e.g., capability, scalability, multipath, NLOS, device heterogeneity, and privacy) and discusses the potential development trends.-
dcterms.accessRightsembargoed accessen_US
dcterms.bibliographicCitationInformation fusion, June 2025, v. 118, 102992-
dcterms.isPartOfInformation fusion-
dcterms.issued2025-06-
dc.identifier.scopus2-s2.0-85217376887-
dc.identifier.eissn1872-6305-
dc.identifier.artn102992-
dc.description.validate202602 bcjz-
dc.description.oaNot applicableen_US
dc.identifier.SubFormIDG000827/2025-11en_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThis work was supported by The Hong Kong Polytechnic University (P0045937); OPEN RESEARCH FUND OF STATE KEY LABORATORY OF INFORMATION ENGINEERING IN SURVEYING, MAPPING AND REMOTE SENSING, WUHAN UNIVERSITY (23P03).en_US
dc.description.pubStatusPublisheden_US
dc.date.embargo2027-06-30en_US
dc.description.oaCategoryGreen (AAM)en_US
Appears in Collections:Journal/Magazine Article
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Embargo End Date 2027-06-30
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