An Indoor Positioning Algorithm Based on Fingerprint and Mobility Prediction in RSS Fluctuation-Prone WLANs
Journal
IEEE Transactions on Systems, Man, and Cybernetics: Systems
Journal Volume
51
Journal Issue
5
Pages
2926-2936
Date Issued
2021
Author(s)
Abstract
The creation of context-Aware services in pervasive computing environments has driven the wide development of wireless local area network (WLAN)-based indoor positioning systems. One of the main challenges in WLAN-based indoor positioning is the severe fluctuation of received signal strength (RSS), which may cause the RSS patterns to be mismatched and the positioning to be inaccurate. In this paper, an indoor positioning algorithm that combines the fingerprint scheme with mobility prediction is proposed. Since the mobility prediction is performed according to the moving speed and direction of the mobile client, the resulting location estimation is more stable compared to the use of RSS alone. Experimental results show that the proposed positioning algorithm can mitigate the impact of the RSS fluctuation and has better positioning accuracy and stability than previous fingerprint-based approaches. ? 2013 IEEE.
Subjects
Clustering algorithms; Forecasting; Information services; Mobile computing; Ubiquitous computing; Wireless local area networks (WLAN); Context aware services; Indoor positioning; Location estimation; Mobility predictions; Pervasive computing environment; Positioning accuracy; Positioning algorithms; Received signal strength; Indoor positioning systems
SDGs
Type
journal article