Proceedings of the 2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018)

A weighted centroid localization algorithm based on RSSI adaptive value coupled with two norm improvements

Authors
Chao Cheng, Zhi-yang Jiang
Corresponding Author
Chao Cheng
Available Online May 2018.
DOI
https://doi.org/10.2991/amcce-18.2018.56How to use a DOI?
Keywords
centroid, adaptive value, localization algorithm, signal strength,
Abstract
This paper proposes an improved localization algorithm based on signal strength (RSSI) adaptive value and two norm. In the localization process of the algorithm, the RSSI values as a direction vector, meet is qualitative, additivity is homogeneous and times, the RSSI values as a function with the concept of ‘length’.In the actual positioning of the finite dimensional space, meet the Minkowski theorem and Cauchy convergence principle. The adaptive value and the second norm can effectively reduce the error of the weight and improve the positioning accuracy of the node. Through MATLAB simulation, the improved average positioning accuracy of this paper improved by 1.675m compared with the traditional centroid positioning algorithm, and the optimization rate reached 52.8%, which proves that the improved algorithm has some reference significance in positioning research.
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Proceedings
2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018)
Part of series
Advances in Engineering Research
Publication Date
May 2018
ISBN
978-94-6252-508-5
ISSN
2352-5401
DOI
https://doi.org/10.2991/amcce-18.2018.56How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Chao Cheng
AU  - Zhi-yang Jiang
PY  - 2018/05
DA  - 2018/05
TI  - A weighted centroid localization algorithm based on RSSI adaptive value coupled with two norm improvements
BT  - 2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018)
PB  - Atlantis Press
SN  - 2352-5401
UR  - https://doi.org/10.2991/amcce-18.2018.56
DO  - https://doi.org/10.2991/amcce-18.2018.56
ID  - Cheng2018/05
ER  -