A central difference Kalman filter(CDKF) with strong tracking behavior is proposed to overcome the problem
that extended Kalman filter(EKF) decreases in accuracy, even divergences when integrated navigation system has model
uncertainty. Strong tracking CDKF views strong tracking filter(STF) as the basic theory framework and makes central
difference transformation take place of calculating nonlinear function Jacobian matrix, so it combines strong robustness of
STF with high accuracy and easy implementation of central difference transformation. The proposed strong tracking CDKF
can avoid filtering failure of EKF while system model is uncertain. Simulation results show the effectiveness of the strong
tracking CDKF.