Flight path reconstruction using extended kalman filtering techniques

An algorithm for the flight path reconstruction of state variables and for estimation of unknown constant bias and scale factor errors in measured data using extended Kalman filter and fixed interval smoother - has been developed. The models are based on the six-degree-of freedom kinematic equations relating measured aircraft responses. The technique is demonstrated with the aid of typical examples using flight test data. Also some sensitivity studies on the variation of noise covariance matrices have been carried out. The results of FPR using extended Kalman filter and maximum likelihood methods are presented in this13; document. Finally aerodynamic estimation has been carried out with a simple linear model on differnt data sets namely (i) flight measured data not corrected for bias and scale factor errors, (ii) using EKF corrected data and (iii) using ML corrected data