Research the estimated algorithm of the Doppler frequency shift based on adaptive fading EKF with the innovation consequence

The high-speed movement of missiles signal tracking system is strongly nonlinear systems. So while the system model can not be accurately established or the model error changes with time, the traditional extended Kalman filter (EKF) and its improved algorithm have large estimated errors and even bring filter divergence for estimating signal Doppler shift (frequency offset). In order to solve the above problem, a new adaptive fading extended Kalman filtering (AFEKF) method is put for ward based on the real time estimation of the covariance matrix of system noise using the innovation sequences. However, existing solver fading factor method too many constraints and the cumbersome calculation process, so it is not conducive to the missile signal tracking application. The small amount of calculation, and improve the reliability of the filtering algorithm, simulation results show the effectiveness of the method.