Aerodynamic parameters identification based on special excitation signals and filter error method

Due to the complicated flight environment, identification of aerodynamic parameters in hypersonic flight vehicle (HFV) must be studied deeply. In this paper, the aerodynamic parameter identification problem in the HFV longitudinal model is studied. Firstly, excitation signals are composed of a sum of sinusoidal signals and then imposed on the elevation rudder. The excitation signals have the optimal peak factor and can be implemented independently to multiple channels, so that the data are met with the identifiability requirement. Secondly, because the hypersonic vehicle model is nonlinear and unstable under open loop control, filter error method (FEM) is used to identify the aerodynamic parameters. Through the extended Kalman filter (EKF), the innovation and covariance matrices related with the aerodynamic parameters are estimated. Thus, aerodynamic parameters can be identified by this algorithm. Finally, FEM is compared with the equation error method (EEM) and the simulation proves the effectiveness of FEM.