A Wi-Fi Wireless Localization Method Based on Local Linear Regression and Position Weighting

DOI

10.2991/icmmita-16.2016.169How to use a DOI?

Keywords

Wi-Fi; RSSI; Indoor localization; Local linear regression; Position weighting.

Abstract

A kind of Wi-Fi wireless location system has been designed and implemented in this research. The system is based on a combined method of local linear regression and position weighting, which develops the traditional ranging algorithm based on RSSI and improves the positioning accuracy. The result shows that the expectation of positioning error is about 2 meters. The error in 83% of the samples is within 3 meters and less than 6 meters in 98%, which shows that the combined method of local linear regression and distributed position weighting can effectively control error range and improve positioning accuracy. With the popularity of indoor wireless routing and mobile phone hotspot, the system will have a very broad application prospects for indoor localization.

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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TY  - CONF
AU  - Yongjun Zhang
AU  - Haixu Guo
PY  - 2017/01
DA  - 2017/01
TI  - A Wi-Fi Wireless Localization Method Based on Local Linear Regression and Position Weighting
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications
PB  - Atlantis Press
SP  - 911
EP  - 918
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmita-16.2016.169
DO  - 10.2991/icmmita-16.2016.169
ID  - Zhang2017/01
ER  -