Aircraft parameter estimation by estimation-before-modelling technique
The use of the estímation-before-modellíng (EBM) two step identification procedure for the determination of aircraft aerodynamic derivatives from flight test data is analysed and illustrated. In the first step of the identification procedure the usual Extended Kalman Filter (EKF) associated with the Modified Bryson-Frazíer (MBF) smoother is compared with a new alterative filtering and smoothing process. The new smoother is simpler and less computationally demanding than the MBF smoother. However, its main advantage is that it enables simultaneous data smoothing with state derivative estimation, thereby avoiding the need for a separate differentiation algorithm. The new smoother differentiator has an important feature that is the determination of the noise characteristics of the measurement signal under analysis prior to the smoothing process. This is done by variance matching between the theoretical and measured autocorrelation of the innovation process generated by a Kalman filter. The new technique is compared with the old one by determining the aerodynamic models for a EMB-312 Tucano dutch roll manoeuvre. It is demonstrated that the new smoother may be used to replace the MBF. Otherwise the new technique is used in the analysis of the Handley Page Jetstream-100 aircraft low speed controls free phugoid trying to identify the contribution of the power Variation observed during the phugoid to the stability of the oscillation. Finally the models obtained from the phugoid analysis are reprocessed using the Total Least Square regression and the results are compared with those from the ordinary Least Square formulation.