Bluetooth positioning based on weighted K-nearest neighbors and adaptive bandwidth mean shift

被引：11

作者：

Wang, Qi ^{[1
]}

Sun, Rui ^{[1
]}

Zhang, Xiangde ^{[1
]}

Sun, Yanrui ^{[1
]}

Lu, Xiaojun ^{[1
]}

机构：

[1] Northeastern Univ, Dept Math, Shenyang, Peoples R China

来源：

INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS | 2017年 / 13卷 / 05期

关键词：

Indoor positioning; Bluetooth; weighted K-nearest neighbors; adaptive bandwidth mean shift; SYSTEM;

D O I：

10.1177/1550147717706681

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Bluetooth positioning is an important and challenging topic in indoor positioning. Although a lot of algorithms have been proposed for this problem, it is still not solved perfectly because of the instable signal strengths of Bluetooth. To improve the performance of Bluetooth positioning, this article proposes a coarse-to-fine positioning method based on weighted K-nearest neighbors and adaptive bandwidth mean shift. The method first employs weighted K-nearest neighbors to generate multi-candidate locations. Then, the testing position is obtained by applying adaptive bandwidth mean shift to the multi-candidate locations, which is used to search for the maximum density of the candidate locations. Experimental result indicates that the proposed method improves the performance of Bluetooth positioning.

引用

页数：8

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