State Estimation of Reentry Target Based on Divided Difference Filter
Chen Fang · Journal of Xi'an Technological University · 2011
State estimation of reentry ballistic target is a complex nonlinear problem.The large error of state estimation of reentry ballistic target,even divergence in the EKF is introduced.In order to improve the estimation accuracy,the divided difference filter(DDF) is used to estimate the state of reentry target with unknown ballistic coefficient.In the DDF algorithm,the state estimation and covariance are obtained by using the second-order multidimensional stirling interpolation polynomial to approximate the nonlinear state and measurement equation.The DDF algorithm is simple,free-derivative,decreasing the computational complexity.Monte Carlo simulation results indicate that the DDF algorithm can decrease the estimation error of the state estimation and improve the state accuracy.Moreover,the running time of the DDF is much less than that of the UKF.