Title :
UAV Attitude Estimation Using Unscented Kalman Filter and TRIAD
Author :
De Marina, Hector Garcia ; Pereda, Fernando J. ; Giron-Sierra, Jose M. ; Espinosa, Felipe
Author_Institution :
Dept. of Comput. Archit. & Automatics, Complutense Univ. of Madrid, Madrid, Spain
Abstract :
A main problem in autonomous vehicles in general, and in unmanned aerial vehicles (UAVs) in particular, is the determination of the attitude angles. A novel method to estimate these angles using off-the-shelf components is presented. This paper introduces an attitude heading reference system (AHRS) based on the unscented Kalman filter (UKF) using the three-axis attitude determination (TRIAD) algorithm as the observation model. The performance of the method is assessed through simulations and compared to an AHRS based on the extended Kalman filter (EKF). The paper presents field experiment results using a real fixed-wing UAV. The results show good real-time performance with low computational cost in a microcontroller.
Keywords :
Kalman filters; attitude control; autonomous aerial vehicles; microcontrollers; nonlinear filters; AHRS; EKF; TRIAD; UAV attitude estimation; attitude heading reference system; extended Kalman filter; low computational cost; microcontroller; observation model; off-the-shelf components; real fixed-wing UAV; three-axis attitude determination algorithm; unmanned aerial vehicles; unscented Kalman filter; Accelerometers; Kalman filters; Magnetometers; Mathematical model; Quaternions; Unmanned aerial vehicles; Attitude heading reference system (AHRS); extended Kalman filter (EKF); three-axis attitude determination (TRIAD); unmanned aerial vehicle (UAV); unscented Kalman filter (UKF);
Journal_Title :
Industrial Electronics, IEEE Transactions on
DOI :
10.1109/TIE.2011.2163913
