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

Abstract

A technique was 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 (HARV) were conducted at 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. The state and observation equations used by the Kalman filter are briefly developed and it is shown how the state and measurement covariance matrices were determined from flight data. Flight data are used to show the results of the technique and these results are compared to an independent measurement source. This technique is applicable to both postflight and real-time processing of data