Aircraft guidance instrumentation error estimation based on neural network method

To satisfy the timely estimation requirement of aircraft fall point deviation, the nonlinear function approximation function of back propagation neural network was adopted to estimate inertial instrument bias effect on aircraft accumulative guidance system error. According to coefficients of inertial instrument model and trajectory parameters, the dominant coefficients and corresponding guidance instruments error are selected as neutral network training input-output sample. Once appropriate network weights and threshold values are fixed, the complicated aircraft fall point precision analysis procedure can be substituted.