Indoor Localization Based on Optimized KNN
Xuanyu Zhu
Network and Communication Technologies, 2021, vol. 5, issue 2, 34
Abstract:
In recent years, with the continuous development of the economic situation, the price of low-end smart phones continues to reduce, the coverage of wireless local area network (WLAN) continues to improve, and individual users pay more and more attention to the real-time information around them, so indoor positioning technology has become a research hotspot. Among them, the indoor positioning based on the location fingerprint method quickly becomes the “Navigator” of indoor positioning direction by virtue of the simplicity of layout, the cost reduction of hardware facilities and the accuracy of positioning effect. However, the traditional indoor positioning methods usually rely on WiFi signal and KNN algorithm. When the KNN algorithm is implemented, there will be a lot of calculation and heavy workload to establish the location fingerprint database offline, and the efficiency and accuracy of online matching positioning points are low. This paper proposes an OKNN algorithm based on the improved KNN algorithm. By improving the efficiency of matching algorithm, the algorithm indirectly improves the positioning accuracy and optimizes the indoor positioning effect.
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.ccsenet.org/journal/index.php/nct/article/download/0/0/44515/46967 (application/pdf)
http://www.ccsenet.org/journal/index.php/nct/article/view/0/44515 (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ibn:nctjnl:v:5:y:2021:i:2:p:34
Access Statistics for this article
More articles in Network and Communication Technologies from Canadian Center of Science and Education Contact information at EDIRC.
Bibliographic data for series maintained by Canadian Center of Science and Education ().