A CS-SemiUKF Based Algorithm on Trajectory Estimation in Boost Phase

Aiming at improving the computational efficiency of the boost phase trajectory estimation algorithm based on the Current Statistic-Uncented Kalman Filtering (CS-UKF), a CS-SemiUKF based boost phase trajectory algorithm is proposed. According to the characteristics of the CS model, the Linear State Equation is used for state prediction and state covariance matrix prediction, and the Measurement Update phase is still achieved through the Sigma points nonlinear propagation. The simulation shows that, compared with the CS-UKF based boost phase trajectory algorithm, the proposed algorithm is rational and effective, the operation time is reduced by approximately 27% under the condition that the estimation error is equivalent.