Proceedings of the 2016 3rd International Conference on Materials Engineering, Manufacturing Technology and Control

Maximum Likelihood Estimation and Centroiding Hybrid RSSI-based Indoor Positioning

Authors
Shan Liu, Shengliang Peng, Zhi Wang
Corresponding Author
Shan Liu
Available Online April 2016.
DOI
10.2991/icmemtc-16.2016.235How to use a DOI?
Keywords
Wireless positioning; RSSI; maximum likelihood estimation; centroiding algorithm
Abstract

RSSI-based positioning technology suffers from accuracy degradation due to complex indoor environment, and traditional weighted centroid algorithm hardly satisfies people's accuracy requirements. In this paper, a hybrid RSSI based positioning algorithm is proposed. Firstly, maximum likelihood estimation method is used to estimate the rough information of positioning target; then, optimized weighted centroiding algorithm is adopted to obtain its accurate coordinates, which further improves the positioning accuracy. Simulation results have verified the superiority of this hybrid algorithm compared with traditional algorithms.

Copyright
© 2016, 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 2016 3rd International Conference on Materials Engineering, Manufacturing Technology and Control
Series
Advances in Engineering Research
Publication Date
April 2016
ISBN
10.2991/icmemtc-16.2016.235
ISSN
2352-5401
DOI
10.2991/icmemtc-16.2016.235How to use a DOI?
Copyright
© 2016, 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  - Shan Liu
AU  - Shengliang Peng
AU  - Zhi Wang
PY  - 2016/04
DA  - 2016/04
TI  - Maximum Likelihood Estimation and Centroiding Hybrid RSSI-based Indoor Positioning
BT  - Proceedings of the 2016 3rd International Conference on Materials Engineering, Manufacturing Technology and Control
PB  - Atlantis Press
SP  - 1187
EP  - 1192
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmemtc-16.2016.235
DO  - 10.2991/icmemtc-16.2016.235
ID  - Liu2016/04
ER  -