Research On Integrated On-Line Identification And Prediction Method Of Missile Aerodynamic/Atmospheric Parameters

The complex operational environment of the future battlefield puts forward a higher realistic demand for the missile's pre-shot survival capability,penetration capability and strike accuracy.In order to achieve rapid launch,ensure the flight quality of the missile during maneuver penetration in the atmosphere,reduce the aerodynamic parameter deviation caused by the difference between the heaven and the earth,and the atmospheric parameter disturbance caused by the complex and versatile flight environment,and improve the missile's strike accuracy and intelligence level,the real-time accurate acquisition of aerodynamic parameters and atmospheric parameters of missiles is studied systematically in this paper.The online identification and prediction methods of aerodynamic/atmospheric parameters are systematically studied.The intrinsic relationship between aerodynamic parameters,atmospheric parameters and missile dynamics system is studied and modeled.A six-degree-of-freedom motion model of a plane-symmetric missile that meets the identification requirements is established.The multi-collinearity diagnosis of the aerodynamic parameter model candidates was carried out by the condition number method.The stepwise regression method was used to optimize the model candidates,and the aerodynamic model structure and the aerodynamic parameters to be identified were established.The relationship between atmospheric parameters and missile motion state parameters is analyzed,and the atmospheric parameter model including wind speed influence is established.The analytical expression between the atmospheric parameter change rate and the force and flight state of the missile is derived.The integrated online identification method of pneumatic/atmospheric parameters based on navigation information is studied.The extended Kalman filter(EKF),unscented Kalman filter(UKF),and unscented Kalman filter(AUKF)are used to satisfy the online demand filter algorithm.The performance of the three filter algorithms is theoretically compared and simulated.The result analysis establishes AUKF as the identification algorithm of this paper.The theory of parameter identifiability is studied.The parameter identifiability analysis criterion based on sensitivity index is proposed.The specific identification of identifiable parameters and unrecognizable parameters in aerodynamic model is determined by simulation.Based on the mathematical model of missile established in the second chapter,combined with the real-time data output from the navigation system,the design of the integrated online identification filter for aerodynamic/atmospheric parameters was carried out,and the state equations and observation equations needed for identification were established.The simulation results show that the integrated online identification of aerodynamic/atmospheric parameters based on navigation information has higher accuracy and better real-time performance in obtaining aerodynamic parameters and atmospheric parameters.The integrated online identification method of pneumatic/atmospheric full parameters under wind disturbance conditions is studied.The pressure model and parameter solving method of the embedded atmospheric data system(FADS)were simulated and verified,and the theoretical research on the FADS system in the pressure hole layout was insufficient.The blunt body missile was taken as an example and the pressure was applied.The research on sensor layout optimization uses flow field simulation to verify the performance of the optimization scheme.By integrating the real-time information given by the navigation and FADS system,a pneumatic/atmospheric full-parameter integrated online identification filter under wind disturbance conditions is designed,real-time accurate acquisition of aerodynamic parameters and atmospheric parameters is realized,and the algorithm is verified by simulation.Effectiveness.A parameter prediction strategy and method based on online identification is proposed.After obtaining the wind speed,density and temperature solution values at current and past time points,the recursive least squares method of fading memory is used to estimate the parameters in the model during flight,and the parameter deviation prediction model is established.The high level of information provided by the plan enables online prediction of wind speed,density and temperature in the future.The work of this paper can provide technical and method support for real-time accurate acquisition of aerodynamic parameters and atmospheric parameters of aircraft in the atmosphere.It can provide reference for the research of online mission planning,non-procedural guidance control,target tracking and drop prediction.