Proceedings of the 3rd International Conference on Mechatronics, Robotics and Automation

Multi-sensor Data Fusion Based on Biased Estimation Method for Wind Speed Measurement

Authors
Xingjia Yao, Yingbo Wang, Wei Wu, Liao Jun
Corresponding Author
Xingjia Yao
Available Online April 2015.
DOI
https://doi.org/10.2991/icmra-15.2015.49How to use a DOI?
Keywords
wind sensor; data fusion; biased estimation; wind speed measurement
Abstract
Multi-sensor data fusion techniques combine data from multiple sensors and related information to achieve more specific inferences compared with using a single, independent sensor. In order to make full use of the information collected by multi-sensor and to increase the accuracy of wind speed, a wind speed measurement method with data fusion based on biased estimation is proposed in this paper. Firstly, different kind of wind speed measurement methods is introduced. Secondly, biased measurement is presented based on ridge estimation, and a quantitative description method evaluating the reliability of the measurement data is proposed. The biased measurement reliability superior to the unbiased one is also verified. Finally, a huge amount of wind speed data illustrates that the presented method is effective.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
3rd International Conference on Mechatronics, Robotics and Automation
Part of series
Advances in Computer Science Research
Publication Date
April 2015
ISBN
978-94-62520-76-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/icmra-15.2015.49How 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  - Xingjia Yao
AU  - Yingbo Wang
AU  - Wei Wu
AU  - Liao Jun
PY  - 2015/04
DA  - 2015/04
TI  - Multi-sensor Data Fusion Based on Biased Estimation Method for Wind Speed Measurement
BT  - 3rd International Conference on Mechatronics, Robotics and Automation
PB  - Atlantis Press
SP  - 246
EP  - 251
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmra-15.2015.49
DO  - https://doi.org/10.2991/icmra-15.2015.49
ID  - Yao2015/04
ER  -