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A novel parameter and state joint estimation method of reentry ballistic targets

In this paper, the reentry phase tracking problem of the ballistic missile for the ground-based anti-missile radar is considered, and a novel parameter and state joint estimation method based on the unscented Kalman filter (UKF) is present. The innovation of this thesis lies in using the Dynamic-Singer model and the 1st order Markov model as the state model of the UKF. The Dynamic-Singer model consists of the reentry ballistic missile dynamic model which is built on the earth-centered-earth-fixed (ECEF) coordinate system and the Singer model which is introduced to describe the maneuverability characteristic of the target in the reentry phase. The 1st order Markov process is used to model the mass-to-drag ratio which is an unknown parameter and usually important to the target recognizing. The presented method is easy to use for data process engineers in the practical radar system, and its performance is verified by simulations.