Aerodynamic Statistics-Based Trajectory Estimation of Hypersonic Maneuvering Target
Yunpeng Cheng, Shuo Tang, Shi Lyu, Manqiao Wu, Qiao Hao
Abstract
Trajectory tracking and estimation of hypersonic glide vehicles (HGVs) is a very challenging issue in the defense systems. Insufficient knowledge about the HGV and inaccurate dynamic models for the accelerating HGV are the main challenges in this regard. In the present study, an integrated nonlinear Markov acceleration model is established to formulate the nonlinear dynamic characteristics of HGVs. Since the aerodynamic accelerations of the HGV are dominant and the corresponding aerodynamic coefficients are unknown, a statistics-based aerodynamic model is proposed. The proposed aerodynamic model is capable of providing primary information of the aerodynamic characteristics even without knowing the configuration of the HGV. Then, considering the maneuver mode of the vehicle, the iterative extended Kalman filter (IEKF) is applied to track the trajectory of the HGV by using the proposed model. Obtained results from the numerical simulation for the equilibrium glide mode and skip maneuver mode indicate that the proposed model can effectively improve the velocity estimation accuracy by about 40%-50% and acceleration estimation accuracy by about 20%-50% in the given examples.