Reentry Trajectory Estimating And Tracking For Hypersonic Vehicle

With the development of aerospace, hypersonic reentry tracking based on the radar become increasingly important. Accurate measuring, tracking and forecasting reentry trajectory based on the ground-based radar is the infrastructure and core for the research of warning and interception. Target tracking usually use classical Kalman Filter. However, due to the strong nonlinear characteristic of hypersonic reentry motion, filtering algorithm needs to be improved to solve the nonlinear problem. This paper focuses on the trajectory estimating and tracking of the hypersonic vehicle including ballistic reentry and maneuvering reentry, at the same time multiple filtering algorithms are applied and the results are contrasted. The main contents and conclusions include:(1) For better tracking the target, the kinetic model and observation model is established for ballistic reentry and maneuvering reentry respectively. The former is under the geocentric coordinate, and the latter is under the radar spherical coordinate.(2) Taking into account the nonlinear characteristic of the reentry tracking model, EKF, UKF and SRCDKF is elaborated which can be applied to the nonlinear problem, and the above three methods are also implemented in software. Due to the uncertainty of the model, the fusion algorithm of IMM and UKF is studied. In addition, in order to evaluate the superiority and inferiority of the model and filtering algorithm, tracking performance assessment criteria is proposed.(3) Within the radar noise, simulation analysis of trajectory tracking with known and fixed ballistic coefficient, and simulation analysis and ballistic coefficient estimation are completed with unknown ballistic coefficient. Influence about the different update rate of the radar and the trajectory tracking is researched. The simulation show that, EKF has the poorest performance; UKF is similar to SRCDKF in terms of tracking results, while the running time increases successively; faster radar data update rate could achieve higher estimation accuracy and convergence speed. At last, IMM-UKF simulation under the uncertain model indicates the above conclusion.(4) For CAV-L, the simulation analysis of the jumping maneuvers and quasi-equilibrium gliding maneuvers have been studied. Result shows that the maneuvering reentry trajectory is able to be tracked well with the UKF and SRCDKF algorithm, but the real-time estimation of aerodynamic coefficient is not very well.This paper has studied trajectory estimation and tracking of the hypersonic reentry vehicle, actually the nature is a trajectory tracking filtering under uncertain factor. The result can provide a theoretical reference on tracking and positioning the high-speed reentry target.