Strong tracking CDKF and application for integrated navigation

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.