A Multi-sensor Data Fusion Algorithm Based on Unscented Kalman Filter for the Attitude Estimation of UAV
Aiming at the low accuracy of the inertial measurement unit and the error of the traditional attitude estimation algorithm, a UAV attitude estimation algorithm based on Unscented Kalman Filter (UKF) is proposed. The Euler angle method is used to describe the attitude algorithm model of the aircraft,...
Uložené v:
| Vydané v: | Journal of physics. Conference series Ročník 1965; číslo 1; s. 12001 - 12006 |
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| Hlavní autori: | , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Bristol
IOP Publishing
01.07.2021
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| Predmet: | |
| ISSN: | 1742-6588, 1742-6596 |
| On-line prístup: | Získať plný text |
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| Shrnutí: | Aiming at the low accuracy of the inertial measurement unit and the error of the traditional attitude estimation algorithm, a UAV attitude estimation algorithm based on Unscented Kalman Filter (UKF) is proposed. The Euler angle method is used to describe the attitude algorithm model of the aircraft, and on this basis, the system state equation and observation equation of the UAV are established; the unscented Kalman filter algorithm is used to achieve the calculation of the attitude angle of the aircraft. By using APM flight control data, the simulation experiment is compared with the traditional attitude estimation algorithm. The experimental results show that the proposed algorithm has a great improvement in reliability and accuracy compared with the attitude estimation algorithm using extended Kalman filter (EKF). |
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| Bibliografia: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 1742-6588 1742-6596 |
| DOI: | 10.1088/1742-6596/1965/1/012001 |