Aircraft attitude estimation using an error state Kalman filter in the navigation coordinate system
When the traditional error-state Kalman filter algorithm is used for aircraft attitude estimation without heading reference,significant errors can occur due to inaccurate linearization. To address this issue,this paper proposes an error-state Kalman filter algorithm based on the navigation coordinate system (NCS-ESKF). An aircraft attitude estimation system is designed,and both indoor static turntable experiments and DA40 airborne flight experiments with a general aviation aircraft are conducted. Experimental results show that,compared to three traditional algorithms,the proposed NCS-ESKF algorithm produces smaller errors,with mean absolute errors (MAE) for roll and pitch angles of just 0.809° and 0.934°,respectively. During the taxiing and flight phases of the airborne experiments,a segmented threshold method was employed to set different horizontal maneuvering acceleration thresholds,resulting in MAEs of 0.954° for roll and 0.867° for pitch. This effectively improves the accuracy of aircraft attitude estimation. The NCS-ESKF algorithm significantly reduces estimation errors and enhances aircraft attitude estimation performance,contributing to improved stability in flight control for general aviation aircraft.
attitude estimationerror state Kalman filternavigation coordinate systemflight experimentsmaneuver acceleration threshold
万方数据
维普
