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

Volume

59

Issue

11

fYear

2012

Firstpage

4465

Lastpage

4474

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);

fLanguage

English

Journal_Title

Industrial Electronics, IEEE Transactions on

Publisher

ieee

ISSN

0278-0046

Type

jour

DOI

10.1109/TIE.2011.2163913

Filename

5977026