Wi-Fi Fingerprint-Based Indoor Positioning: Recent Advances and Comparisons
Abstract
The growing commercial interest in indoor location-based services (ILBS) has spurred recent development of many indoor positioning techniques. Due to the absence of Global Positioning System (GPS) signal, many other signals have been proposed for indoor usage. Among them, Wi-Fi (802.11) emerges as a promising one due to the pervasive deployment of wireless LANs (WLANs). In particular, Wi-Fi fingerprinting has been attracting much attention recently because it does not require line-of-sight measurement of access points (APs) and achieves high applicability in complex indoor environment. This survey overviews recent advances on two major areas of Wi-Fi fingerprint localization: advanced localization techniques and efficient system deployment. Regarding advanced techniques to localize users, we present how to make use of temporal or spatial signal patterns, user collaboration, and motion sensors. Regarding efficient system deployment, we discuss recent advances on reducing offline labor-intensive survey, adapting to fingerprint changes, calibrating heterogeneous devices for signal collection, and achieving energy efficiency for smartphones. We study and compare the approaches through our deployment experiences, and discuss some future directions.
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Indoor positioning in public spaces on transport networks is challenging because radio signals are subject to reflection, diffraction, scattering, attenuation by people, and ambient humidity.
“Indoor positioning in public spaces on the transport network is a challenge for several reasons: during propagation, the radio signal is subject to reflection, diffraction and scattering due to the architectural elements that exist in that space. To these effects we also have to add signal attenuation due to the presence of people, which may be a mass presence of people in public spaces such as”
From Study on an Indoor Positioning System for Harsh Environments Based on Wi-Fi and Bluetooth Low Energy (2017) · cites this paper as [7]
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- Authors
- He, S., & Chan, S.-H. G.
- Affiliations
- Hong Kong University of Science and Technology (HK)
- Venue
- IEEE Communications Surveys & Tutorials
- Published
- 2016
- Volume
- 18
- Issue
- 1
- Pages
- 466-490
- ISSN
- 1553-877X (ISSN-L)
- OpenAlex
- W2278572312
- Cited by
- 1,355
- References
- 0
- Citations by year
- 2026: 78 · 2025: 84 · 2024: 86 · 2023: 104 · 2022: 109 · 2021: 134 · 2020: 182 · 2019: 228 · 2018: 191 · 2017: 113 · 2016: 42 · 2015: 2 · 2012: 1
- FWCI
- 55.94
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Communications Surveys & Tutorials (publishedVersion)
- Rare & Special e-Zone (The Hong Kong University of Science and Technology) (submittedVersion)
- Funders
- The Hong Kong R&D Center for Logistics and Supply Chain Management Enabling Technologies (ITP/034/12LP)
- Hong Kong Research Grant Council (RGC) General Research Fund (610713)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Indoor and Outdoor Localization Technologies
- Social Sciences › Transportation › Human Mobility and Location-Based Analysis
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Optical Wireless Communication Technologies
- Keywords
- Wi-Fi fingerprinting, indoor positioning, indoor location-based services, Wi-Fi positioning, signal patterns, user cooperation, motion sensors, energy efficiency, smartphones, wireless LAN
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