Estimation of longitudinal aerodynamic coefficients of a technology demonstrator aircraft using modified maximum likelihood algorithm

Parameter estimation has become a strong tool in the aircraft industry capable of predicting stability and control derivatives even in the presence of noise and uncertainties. The modern instrumentation system along with the computational facilities ensures the simulation of complex flight regimes and parameter extraction with higher precision. In this paper, estimation of stability and control derivatives for the longitudinal dynamics of a Technology Demonstrator Aircraft (TDA) under wings level steady flight is presented. Modified maximum likelihood estimation method (MMLE) makes use of Kalman filter to estimate the system states, from the noisy measurements. A comparative analysis of the estimated parameters is done with that from Maximum likelihood method (MLE) for both Gauss-Newton (GN) and Levenberg-Marquardt (LM) methods of parameter updating. Cramer-Rao bounds and the Theil´s inequality coefficients validate the model being estimated.