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Open AccessArticle

An Adaptive Weighted KNN Positioning Method Based on Omnidirectional Fingerprint Database and Twice Affinity Propagation Clustering

NASG Key Laboratory of Land Environment and Disaster Monitoring, China University of Mining and Technology, Xuzhou 221116, China
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Sensors 2018, 18(8), 2502; https://doi.org/10.3390/s18082502
Received: 8 May 2018 / Revised: 9 July 2018 / Accepted: 27 July 2018 / Published: 1 August 2018
(This article belongs to the Special Issue Selected Papers from UPINLBS 2018)
The human body has a great influence on Wi-Fi signal power. A fixed K value leads to localization errors for the K-nearest neighbor (KNN) algorithm. To address these problems, we present an adaptive weighted KNN positioning method based on an omnidirectional fingerprint database (ODFD) and twice affinity propagation clustering. Firstly, an OFPD is proposed to alleviate body’s sheltering impact on signal, which includes position, orientation and the sequence of mean received signal strength (RSS) at each reference point (RP). Secondly, affinity propagation clustering (APC) algorithm is introduced on the offline stage based on the fusion of signal-domain distance and position-domain distance. Finally, adaptive weighted KNN algorithm based on APC is proposed for estimating user’s position during online stage. K initial RPs can be obtained by KNN, then they are clustered by APC algorithm based on their position-domain distances. The most probable sub-cluster is reserved by the comparison of RPs’ number and signal-domain distance between sub-cluster center and the online RSS readings. The weighted average coordinates in the remaining sub-cluster can be estimated. We have implemented the proposed method with the mean error of 2.2 m, the root mean square error of 1.5 m. Experimental results show that our proposed method outperforms traditional fingerprinting methods. View Full-Text
Keywords: indoor positioning; adaptive weighted algorithm; K-nearest neighbor; omnidirectional fingerprint database; affinity propagation clustering indoor positioning; adaptive weighted algorithm; K-nearest neighbor; omnidirectional fingerprint database; affinity propagation clustering
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Bi, J.; Wang, Y.; Li, X.; Qi, H.; Cao, H.; Xu, S. An Adaptive Weighted KNN Positioning Method Based on Omnidirectional Fingerprint Database and Twice Affinity Propagation Clustering. Sensors 2018, 18, 2502.

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