Indoor Localization Based on Optimized KNN

Zhu, Xuanyu (2020) Indoor Localization Based on Optimized KNN. Network and Communication Technologies, 5 (2). p. 34. ISSN 1927-064X

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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.

Item Type: Article
Subjects: AP Academic Press > Multidisciplinary
Depositing User: Unnamed user with email support@apacademicpress.com
Date Deposited: 06 Jun 2023 06:48
Last Modified: 15 Oct 2024 10:16
URI: http://info.openarchivespress.com/id/eprint/1456

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