基于RK-UKF算法的再入目标质阻比估计

Estimation of Reentry Target’s Mass-to-Drag Ratio Based on RK-UKF

针对再入目标质阻比实时估计的问题,根据目标的三维再入运动模型及量测模型,提出了一种基于龙格-库塔(Runge-Kutta)积分的不敏卡尔曼滤波(UKF)算法(RK-UKF)的再入目标质阻比估计方法,给出了RK-UKF算法与扩展卡尔曼滤波(EKF)算法和不敏卡尔曼滤波算法的仿真比较.仿真结果表明,RK-UKF算法可实现对再入目标的高精度跟踪和其质阻比快速稳定的估计.

In consideration of the problem of reentry target’s mass-to-drag ratio,a method for reentry target’s mass-to-drag ratio estimation based on the Runge-Kutta integral unscented Kalman filter（RK-UKF） is presented,on the basis of the 3D reentry motion model and its measurement model.And the simulation compari-son for the algorithms of RK-UKF,EKF and UKF is given in this paper.Simulation results show that the high pre-cision tracking of the reentry target and the fast and stable estimation of its mass-to-drag ratio can be realized by using the RK-UKF algorithm.