Maximum Likelihood Estimation of Parameters in Nonlinear Flight Mechanics Systems

Abstract

Two methods for maximum likelihood estimation of flight mechanics parameters have been developed. They are applicable to system models which may be nonlinear in the state and control variables as well as in the parameters to be estimated. The optimization problem has been solved by using both minimum search methods and quasi-linearization method. Advantages and disadvantages of both methods are discussed. In the latter case the need for deriving explicit sensitivity equations has been overcome by approximating the sensitivity coefficients by numerical differences. This results in a computationally attractive implementation of the estimation method for routine applications to general nonlinear systems. These techniques have been applied to the problems of kinematic consistency checking of flight test data as well as estimation of aerodynamic derivatives.