We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
A Fast Adaptive-Gain Complementary Filter Algorithm for Attitude Estimation of an Unmanned Aerial Vehicle.
- Authors
Yang, Qing-quan; Sun, Ling-ling; Yang, Longzhao
- Abstract
A novel fast adaptive-gain complementary filter algorithm is developed for Unmanned Aerial Vehicle (UAV) attitude estimation. This approach provides an accurate, robust and simple method for attitude estimation with minimised attitude errors and reduced computation. UAV attitude data retrieved from accelerometer data is transformed to the solution of a linearly discrete dynamic system. A novel complementary filter is designed to fuse accelerometer and gyroscope data, with a self-adjusted gain to achieve a good performance in accuracy. The performance of the proposed algorithm is compared with an Adaptive-gain Complementary Filter (ACF) and Extended Kalman Filtering (EKF). Simulation and experimental results show that the accuracy of the proposed filter has the same performance as an EKF in high dynamic operating conditions. Therefore, the proposed algorithm can balance accuracy and time consumption, and it has a better price/performance ratio in engineering applications.
- Subjects
DRONE aircraft; ALGORITHMS; KALMAN filtering; MICROELECTROMECHANICAL systems; NANOSATELLITE attitude control systems
- Publication
Journal of Navigation, 2018, Vol 71, Issue 6, p1478
- ISSN
0373-4633
- Publication type
Article
- DOI
10.1017/S0373463318000231