Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)

A Novel Distance Estimation Algorithm for Bluetooth Devices Using RSSI

Authors
Junhua Huang, Song Chai, Nan Yang, Liang Liu
Corresponding Author
Junhua Huang
Available Online June 2017.
DOI
10.2991/caai-17.2017.86How to use a DOI?
Keywords
-bluetooth, distance estimation; RSSI, median filter; Kalman fitler
Abstract

A lot of proximity related Bluetooth applications, such as Bluetooth indoor positioning/navigation and proximity detection, has emerged on market by using Received Signal Strength Index(RSSI). One of the key technology in these application is to estimate distance between Bluetooth devices. In this paper, a distance estimation algorithm is proposed for Bluetooth devices. The RSSI values are first processed using median filter, and then converted to distance values. Finally, Kalman filtering is applied to further reduce noise. Our experiments show that our algorithm has average accuracy of 0.1~0.4m.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)
Series
Advances in Intelligent Systems Research
Publication Date
June 2017
ISBN
10.2991/caai-17.2017.86
ISSN
1951-6851
DOI
10.2991/caai-17.2017.86How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Junhua Huang
AU  - Song Chai
AU  - Nan Yang
AU  - Liang Liu
PY  - 2017/06
DA  - 2017/06
TI  - A Novel Distance Estimation Algorithm for Bluetooth Devices Using RSSI
BT  - Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)
PB  - Atlantis Press
SP  - 379
EP  - 381
SN  - 1951-6851
UR  - https://doi.org/10.2991/caai-17.2017.86
DO  - 10.2991/caai-17.2017.86
ID  - Huang2017/06
ER  -