A comparison of flight input techniques for parameter estimation of highly-augmented aircraft

Abstract

Parameter estimation is an inverse process in which stability derivatives are determined from time history flight data by matching the aircraft mathematical model's computed response with the measured response of the aircraft. Accurate parameter estimation depends mainly on instrumentation and input technique. Input technique is the focus of this thesis in which both classical inputs and optimal inputs were applied under the same flight conditions to the High Angle of Attack Research Vehicle (HARV) at NASA Dryden Flight Research Center. Post flight parameter estimation was conducted in all cases using a maximum likelihood technique to determine estimated of stability and control derivatives and their respective Cramer-Rao bounds. The Cramer-Rao bound is the most useful measure of estimate accuracy when comparing results from different input techniques assuming the same mathematical model and minimization technique were used for the parameter estimates. Comparison of the Cramer-Rao bounds showed that of the four input techniques used for determining parameter estimates, the Dryden single-surface input technique yielded the most accurate parameters for 75 percent of the estimates in all cases. Application of these conclusions in further research can save time and costs.