The Research of Wi-Fi Indoor Positioning Algorithm based on Position Fingerprint

DOI

10.2991/icmmcce-15.2015.522How to use a DOI?

Keywords

Position fingerprint, Indoor positioning, Kalman filter, Probability weighted, Naive Bayes algorithm.

Abstract

To improve the positioning accuracy and robustness of indoor positioning technology, a fingerprint positioning method is proposed based on the Kalman filter and the probability weighted Bayes algorithm. Firstly, the optimal estimation of signal strength is calculated using the prediction and correction model of Kalman filter, and then the position is estimated using the posterior probability weighted Naive Bayes algorithm. The experimental results show that the algorithm based on Kalman filter and the probability weighted Bayes gains pretty good positioning accuracy and robustness.

Copyright

© 2015, 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  - Yujie Liu
AU  - Meng Wu
PY  - 2015/12
DA  - 2015/12
TI  - The Research of Wi-Fi Indoor Positioning Algorithm based on Position Fingerprint
BT  - Proceedings of the 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering 2015
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmcce-15.2015.522
DO  - 10.2991/icmmcce-15.2015.522
ID  - Liu2015/12
ER  -