Development of a Time Domain Identification Algorithm with a Spectral Objective Function

A reliable method has been developed for identifying aerodynamic coefficients and systematic errors in the aircraft measuring system, using the advantages of frequency domain analysis. The parameter identification problem is formulated using maximum likelihood estimation method. The models of object and observation are formulated in time domain and the objective function is defined in frequency domain that is able to decouple the aircraft’s response at different frequencies, effectively mitigating the impact of noise and potential non-linearities inherent in time-domain data. This transformation from time domain to frequency domain also facilitates the identification of delays in measurement system, which are often difficult to estimate accurately in the time domain. A modified Newton’s method is employed to efficiently minimize the objective function in frequency domain, yielding optimal estimates for the lateral aerodynamic derivatives and delays. The effectiveness of this approach is validated through examples of identifying the parameters of a flight vehicle motion model, demonstrating its capability to accurately characterize lateral aircraft dynamics. This method provides a valuable tool for enhancing flight control system design and analysis by enabling more precise modeling of aircraft behavior.