The linearization error, which is propagated in the measurement update of the extend Kalman filter(EKF) and
iterated extended Kalman filter(IEKF), may somewhat degrade the filtering performance. Therefore, an iterated divided
difference filter is proposed, which combines the iterated method and statistically linearization error propagation with the
divided difference filter. This algorithm is applied to state estimation for reentry ballistic target. Simulation results show that,
the proposed method can reduce the influence of the measurement nonlinearity, and higher accuracy of state estimation is
guaranteed.