Preliminary Research On Turbulent Flight State Estimation Based On Flight Data

Atmospheric disturbances such as turbulence seriously affect the flight safety,ride experience and flight quality of civil aviation aircraft.Considering the state redundancy in flight parameters recorded by the flight data recorder,it is a theoretically feasible technical approach to estimate aircraft state and turbulence accurately based on flight data.After researching several state estimation algorithms,this paper made full use of the recorded characteristics of flight data,and selected an adaptive extended Kalman filtering algorithm based on the maximum likelihood criterion to estimate the aircraft state.Furthermore,the extended Kalman filter was used to estimate the three dimensional spatial turbulent wind.The research contents are summarized as follows:(1)The recording and characteristics of flight data,and the factors affecting landing safety were analyzed.The flight data recording system,format,characteristics and its status redundancy were studied.After that,the grey close correlation analysis based on time series and the gray canonical correlation analysis were used to find the quantitative relationship between flight parameters and unsafe events including long landing and hard landing in approach and landing procedure.(2)The aircraft state estimation algorithms were studied.Based on the analysis of extended Kalman filter and unscented Kalman filter,considering the changes of system model and the unknown statistical characteristics of flight data,an adaptive extended Kalman filtering algorithm based on maximum likelihood criterion was studied.The aircraft motion state estimation was taken as an example to analysis algorithm performance and compare the results of three algorithms mentioned.(3)The airflow angle of aircraft was estimated.Taking the different sampling frequency of each flight parameter into account,the non-equal interval theory and the adaptive Kalman filtering algorithm based on the maximum likelihood criterion were used to estimate the attack angle and sideslip angle of aircraft based on the flight dynamics model.What’s more,the estimated results were compared with the results of extended Kalman filter and unscented Kalman filter.(4)A three-dimensional spatial estimation model of turbulence was established based on the von Karman atmospheric turbulence model and the vector triangle relationship between the airspeed,ground speed and wind speed.Three-dimensional turbulent wind with different degrees of light,moderate and severe were estimated by extended Kalman filter.The results show that the effect of adaptive extended Kalman filter algorithm based on the maximum likelihood criterion is better than the other two algorithms for the estimation of aircraft’s motion state and airflow angle.Furthermore,the three-dimensional spatial estimation model of turbulence can achieve preliminary estimation of turbulent wind with the degrees of light and moderate.