A comparison of several nonlinear filters for ballistic missile tracking on re-entry

Abstract

In this paper, ballistic missile tracking on re-entry has been considered. Position, velocity and ballistic coefficient are considered as states of the target. As no prior information about the target shape, mass and area is available, ballistic coefficient of the target has been considered as a state variable. Different type of nonlinear filters such as ensemble Kalman filter (EnKF), unscented Kalman filter (UKF), Gauss-Hermite filter (GHF), sparse-grid Gauss-Hermite filter (SGHF), cubature quadrature Kalman filter (CQKF) are used to estimate states of the target. The performance of all the above mentioned filters has been compared on the basis of estimation accuracy, computational time and missed distance. The 3 points GHF provides lowest miss distance at reasonably low computational time; so GHF-3 is recommended for this problem.