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UAV Attitude Estimation Using Unscented Kalman Filter and TRIAD

2011; Institute of Electrical and Electronics Engineers; Volume: 59; Issue: 11 Linguagem: Inglês

10.1109/tie.2011.2163913

1557-9948

Héctor García de Marina, Fernando J. Pereda, José M. Girón-Sierra, Felipe Espinosa,

Target Tracking and Data Fusion in Sensor Networks

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.