Bayesian Fusion for Indoor Positioning Using Bluetooth Fingerprints

被引：114

作者：

Chen, Liang ^{[1
]}

Pei, Ling ^{[1
]}

Kuusniemi, Heidi ^{[1
]}

Chen, Yuwei ^{[1
]}

Kroger, Tuomo ^{[1
]}

Chen, Ruizhi ^{[1
]}

机构：

[1] Finnish Geodet Inst, Dept Positioning & Nav, Kyrkslatt, Finland

来源：

WIRELESS PERSONAL COMMUNICATIONS | 2013年 / 70卷 / 04期

关键词：

Bayesian fusion; Indoor positioning; Fingerprints; Bluetooth; Motion model;

D O I：

10.1007/s11277-012-0777-1

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

摘要：

This paper studies the use of received signal strength indicators (RSSI) applied to fingerprinting method in a Bluetooth network for indoor positioning. A Bayesian fusion (BF) method is proposed to combine the statistical information from the RSSI measurements and the prior information from a motion model. Indoor field tests are carried out to verify the effectiveness of the method. Test results show that the proposed BF algorithm achieves a horizontal positioning accuracy of about 4.7m on the average, which is about 6 and 7% improvement when compared with Bayesian static estimation and a point Kalman filter method, respectively.

引用

页码：1735 / 1745

页数：11

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