A multi - sensor fusion algorithm for UAV attitude estimation
A multi - sensor fusion algorithm for UAV attitude estimation
- Author(s): H. Che 1 ; G. Wang 2 ; C. Shi 1
- DOI: 10.1049/icp.2021.0410
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- Author(s): H. Che 1 ; G. Wang 2 ; C. Shi 1
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View affiliations
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Affiliations:
1:
First Beijing Key Laboratory of Metro Fire and Passenger Transportation Safety , China Academy of Safety Science and Technology , Beijing, China ;
2: School of Automation , Beijing University of Posts and Telecommunications , Beijing 100876, China
Source:
CSAA/IET International Conference on Aircraft Utility Systems (AUS 2020),
2021
p.
948 – 952
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Affiliations:
1:
First Beijing Key Laboratory of Metro Fire and Passenger Transportation Safety , China Academy of Safety Science and Technology , Beijing, China ;
- Conference: CSAA/IET International Conference on Aircraft Utility Systems (AUS 2020)
- DOI: 10.1049/icp.2021.0410
- ISBN: 978-1-83953-419-5
- Location: Online Conference
- Conference date: 18-21 September 2020
- Format: PDF
Aiming at gyroscope drift and noise disturbance problem in unmanned aerial vehicle (UAV) positioning system, an adaptive gradient descent and complementary filter method based on multi-sensor fusion was proposed. One gradient descent method was first adopted to process the data measured by accelerometer. Then the hybrid filter fusion algorithm is introduced, which fused the gyroscope measurements. At the same time, considering the complexity of flight attitude, the parameters can be adaptively adjusted. Thus the adaptive hybrid filter fusion algorithm can guarantee the optimal attitude estimation in real time for various flight attitudes. The proposed fusion algorithm was tested in inertial dataset. The results showed that the algorithm effectively reduced the interference caused by gyroscope divergence, motion acceleration. Compared with traditional gradient descent and complementary filter fusion algorithm, the algorithm can adjust parameter online in real time, and effectively improved the attitude estimation accuracy.
Inspec keywords: accelerometers; Kalman filters; sensor fusion; gyroscopes; filtering theory; attitude measurement; autonomous aerial vehicles; gradient methods; remotely operated vehicles; attitude control
Subjects: Aerospace control; Interpolation and function approximation (numerical analysis); Optimisation techniques; Computer vision and image processing techniques; Spatial variables measurement; Mobile robots; Spatial variables control; Interpolation and function approximation (numerical analysis); Other topics in statistics; Optical, image and video signal processing; Other topics in statistics; Optimisation techniques; Filtering methods in signal processing; Signal processing theory; Telerobotics