基于集成经验模态分解的弹道导弹关机点估计算法

Estimating Burnout Time of Ballistic Missile Based on Ensemble Empirical Mode Decomposition

落点估计精度是弹道导弹防御系统最重要的性能指标之一,而关机点时刻是落点估计的重要参考数据之一。文中提出一种基于集成经验模态分解的弹道导弹关机点估计算法,该算法首先采用卡尔曼滤波分析主动段的航迹趋势,并粗定出关机点时刻;然后,通过集成经验模态分解进一步提升关机点时刻估计精度;最后,通过仿真实验与常用的滤波估计算法进行了比较。结果表明:文中提出的算法在关机点时刻估计误差和结果得出延迟方面都有一定的改进,对落点估计具有重要的参考价值。

The estimation precision of the impact point is one of the most important performance indexes of the ballistic missile defense system. The burnout time is one of the most important reference data for estimating the impact point. An algorithm based on ensemble empirical mode decomposition(EEMD) for estimating burnout time of ballistic missile is proposed, which firstly analyzes the track trend of the boost phase and estimates a rough burnout time by Kalman filter. Secondly, the precision for burnout time estimation is improved using EEMD. Lastly, the proposed algorithm is compared with several common filtering estimation algorithms in a simulation experiment. The experimental results show that the proposed algorithm makes a certain improvement in the aspect of the estimating error of the burnout time and the delay of the result obtaining, and is very useful for the prediction of impact point.