TY - GEN
T1 - Wind and Airflow Angle Estimation Using an Adaptive Extended Rauch-Tung-Striebel Smoother
AU - Fang, X.
AU - de Visser, C.C.
AU - Pool, D.M.
AU - Holzapfel, Florian
PY - 2022
Y1 - 2022
N2 - This paper proposes a new method that estimates the three-dimensional stochastic wind velocity for an aircraft equipped with a Pitot-static tube and airflow vanes. Since the performance of most state estimators, e.g., the extended Rauch-Tung-Striebel smoother, relies on the process and measurement noise covariance settings, the proposed method employs the expectation-maximization approach to estimate the noise covariance matrices to improve the estimation accuracy. Numerical simulations demonstrated that the proposed method can successfully estimate the noise covariance matrices, especially for the noise covariance of the wind velocity, using the measurement data and reconstruct the wind velocity offline. Additionally, the smoothed true airspeed, angle of attack, and angle of sideslip data are more accurate compared to the direct measurements. This feature is also beneficial for other applications such as the aerodynamic model identifications of aircraft.
AB - This paper proposes a new method that estimates the three-dimensional stochastic wind velocity for an aircraft equipped with a Pitot-static tube and airflow vanes. Since the performance of most state estimators, e.g., the extended Rauch-Tung-Striebel smoother, relies on the process and measurement noise covariance settings, the proposed method employs the expectation-maximization approach to estimate the noise covariance matrices to improve the estimation accuracy. Numerical simulations demonstrated that the proposed method can successfully estimate the noise covariance matrices, especially for the noise covariance of the wind velocity, using the measurement data and reconstruct the wind velocity offline. Additionally, the smoothed true airspeed, angle of attack, and angle of sideslip data are more accurate compared to the direct measurements. This feature is also beneficial for other applications such as the aerodynamic model identifications of aircraft.
UR - http://www.scopus.com/inward/record.url?scp=85123626627&partnerID=8YFLogxK
U2 - 10.2514/6.2022-1399
DO - 10.2514/6.2022-1399
M3 - Conference contribution
T3 - AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2022
BT - AIAA SCITECH 2022 Forum
T2 - AIAA SCITECH 2022 Forum
Y2 - 3 January 2022 through 7 January 2022
ER -