Integration of UWB RSS to Wi-Fi RSS fingerprinting-based indoor positioning system. Issue 1 (31st December 2022)

• Record Type: Journal Article
• Authors: Chong, Alvin-Ming-Song; Yeo, Boon-Chin; Lim, Way-Soong
• Editors: Pratap, Saurabh
• Is Part Of: Cogent engineering. Volume 9:Issue 1(2022)
• Publication Date: 2022-12-31
• Subjects: indoor positioning system (IPS) -- received signal strength (RSS) -- fingerprint -- Wi-Fi -- ultra-wide band (UWB) -- hybrid -- neural network; Engineering -- Periodicals; Technology -- Periodicals; Engineering; Technology; Periodicals; 620
• DOI: 10.1080/23311916.2022.2087364
• Languages: English
• ISSNs: 2331-1916

Abstract

Abstract: Wi-Fi Received Signal Strength (RSS) fingerprinting-based Indoor Positioning System (IPS) is an economical technique due to its implementation from the existing Wi-Fi infrastructure. Nevertheless, it suffers limited positioning accuracy and in recent years, researchers have proposed various approaches to mitigate the problem. Combining different positioning algorithms is a common approach to improve the accuracy which often at the same increase the system algorithm complexity. Meanwhile, combining signals from different wireless technologies for position information is an alternative approach. Recently, Ultra-Wide Band (UWB) stands out among other wireless technologies due to its high positioning accuracy. However, an IPS developed entirely using UWB suffers from high development costs. Thus, this paper has proposed an integration of UWB RSS into Wi-Fi RSS fingerprinting-based IPS to improve the positioning accuracy. Experiments have been conducted in a designated environment equipped with Wi-Fi and UWB anchors. Results show that the positioning accuracy of IPS with the combination of UWB and Wi-Fi is overall better than Wi-Fi-based IPS even there is a reduction of the sampling points of RSS in the indoor environment. On average, the accuracy of IPS with the combination of UWB and Wi-Fi is at least two times more superior than the Wi-Fi-based IPS.