© 2016 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.Maneuver inputs designed for aircraft parameter identification are often applied during the aircraft flies close to a trimmed flight condition at an approximately constant Mach number. Since a fixed wing aircraft has control over its thrust and speed, various maneuver inputs can be applied to identify aerodynamic derivatives at discrete Mach numbers. On the contrary, most agile missile configurations do not have control over their speed, number of flight test trials is fairly limited and flight durations are much less than that of fixed wing aircraft. Therefore the missile aerodynamic parameter identification problem requires a different approach. In this study, the Kalman filter is employed together with measurements and flight path reconstruction outputs modified by the Wiener filter and a complementary filter. The resulting method is applied to the identification of aerodynamic parameters of a supersonic missile, which has large and rapid Mach variations throughout its limited flight duration. First, the originally nonlinear aerodynamic identification problem is reduced to a classical, time-invariant aerodynamic derivative identification problem. Then the derived model is improved by adding Mach derivatives of aerodynamic terms. The resulting parameter identification problem is solved, utilizing an adaptive Kalman filter. The method is tested against a set of uncertainties involving instrumentation errors and noises. Angle of attack reconstruction problems due to instrumentation errors are remedied by applying a complementary filter, which is designed using a predefined but uncertain aerodynamic model. The flight data for parameter identification is generated, simulating a high fidelity six degree of freedom missile model.