AIRCRAFT AIR DATA ESTIMATION USING A MODEL-BASED APPROACH

Air data consists of flight parameters such as pressure altitude, Mach number, angle of attack and angle of sideslip. Traditionally these are derived from measurements of local pressures and local flow angles on the fuselage using external air data probes and vanes. This paper describes the formulation of a Kalman Filter for the estimation of aircraft air data states associated with the pitch aerodynamics. The mathematical model of the aircraft embedded within the Kalman Filter contains the highly non-linear aerodynamic coefficients for the pitch dynamics of the aircraft. A selection of results from a comprehensive simulation assessment are also presented.