Peng Lu1, Fengzhi Dai1,2
1Tianjin University of Science and Technology, China
2Tianjin Tianke Intelligent and Manufacture Technology CO., LTD, China
pp. 195-200
ABSTRACT
As an important research direction in the field of sensors, multi-sensor
data fusion has received greater attention and development in areas such
as robotics and autonomous driving. This paper provides a comprehensive
introduction to the physical model-like and parameter-based data fusion
algorithms that are often used in current engineering. Meanwhile, the process,
steps and recent developments of the weighted average method and the extended
Kalman filter method are highlighted, and multi-sensor data fusion experiments
are conducted for each of the two algorithms. The simulation results prove
that the data fusion algorithm has a good fusion effect.
ARTICLE INFO
Article History
Received 22 November 2021
Accepted 28 March 2022
Keywords
Multi-sensor
Data fusion
Weighted average method
Extended kalman filter
JAALR2406
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