Aircraft parameter identification by the Gauss-Newton method in the frequency domain

Abstract

Abstract A frequency-domain output-error method based on the Gauss-Newton minimization technique has been developed for the estimation of aircraft parameters from flight data. The method has been validated on simulated flight data. The effect of the intensity of measurement noise present in the flight data is studied and the method is shown to work satisfactorily even in the presence of high noise levels. Six different types of rudder and aileron control inputs have been used to generate the flight data; the analysis of such data is carried out to identify the suitable control input forms for the parameter estimation. Results are presented to show the effect of using the ‘packing theorem’ to increase the sparsely sampled frequency data; assigning a priori values to some of the weak parameters; and starting the iteration process with different initial values. Finally, a comparison of the method in the time domain and the frequency domain is presented to point out the relative merits of the latter approach.