Preliminary results from an airdata enhancement algorithm with application to high-angle-of-attack flight

A technique has been developed to improve the fidelity of airdata measurements during dynamic maneuvering. This technique is particularly useful for airdata measured during flight at high angular rates and high angles of attack. To support this research, flight tests using the F-18 high alpha research vehicle were conducted at the NASA Ames Research Center Dryden Flight Research Facility. A Kalman filter was used to combine information from research airdata, linear accelerometers, angular rate gyros, and attitude gyros to determine better estimates of airdata quantities such as angle of attack, angle of sideslip, airspeed, and altitude. This paper briefly develops the state and observation equations used by the Kalman filter and shows how the state and measurement covariance matrices were determined from flight data.