Research Article
Simultaneous Indoor Localization Based on Wi-Fi RSS Fingerprints
@INPROCEEDINGS{10.1007/978-3-030-93709-6_25, author={Nooria Rafie and Bang Wang}, title={Simultaneous Indoor Localization Based on Wi-Fi RSS Fingerprints}, proceedings={Advances of Science and Technology. 9th EAI International Conference, ICAST 2021, Hybrid Event, Bahir Dar, Ethiopia, August 27--29, 2021, Proceedings, Part I}, proceedings_a={ICAST}, year={2022}, month={1}, keywords={Indoor localization Simultaneous localization Wi-Fi Fingerprinting RSS Multidimensional scaling}, doi={10.1007/978-3-030-93709-6_25} }- Nooria Rafie
Bang Wang
Year: 2022
Simultaneous Indoor Localization Based on Wi-Fi RSS Fingerprints
ICAST
Springer
DOI: 10.1007/978-3-030-93709-6_25
Abstract
Indoor localization has been extensively investigated over the last few decades, especially in the industrial area of wireless sensor networks. For indoor positioning, many techniques have been proposed over the Wi-Fi signal’s deployment. Wi-Fi Received Signal Strength (RSS) fingerprinting approach especially the deterministic algorithms have received much attention. However, as the deterministic algorithms use RSS of the test point (TP) by ignoring the other TPs, two or more TPs will take the same location while physically far apart, and the reverse can also be true. Thus, to improve positioning accuracy, this study proposes Wi-Fi RSS fingerprint based simultaneous indoor localization (SIL). The proposed approach was tested on the data collected from Huazhong University of Science and Technology teaching buildings. Experimental results show error reduction upto 9.8%, and 13.2% in MDE (Mean Distance Error) and standard deviation, respectively.
