Trajectory Reconstruction Using Radar Measured Data
Kai Li · Journal of Ballistics · 2011
To effectively use radar measured data to reconstruct actual trajectory,the nonlinear filtering model of trajectory was established considering random wind;the integral predictive Unscented Kalman Filter(UKF)algorithm was developed as a tool for trajectory reconstruction.When the UKF was applied to reconstruct trajectory online,the uncertain initial conditions induced large initial estimated errors of ballistic parameters.A novel and efficient smoother Unscented Rauch-Tung-Striebel Smoother(URTSS)was introduced to solve this problem.By URTSS,the final value of the state and covariance were transmitted back to the initial time,and the optimal estimated trajectory was obtained.Simulation result shows that it is effective to apply UKF method to reconstruct trajectory,and URTSS can reduce estimated errors of ballistic parameters,especially the estimated errors of the projectile muzzle velocity and the wind.The precision of reconstruction of actual trajectory using radar measured data is improved.