基于LSTM的弹道导弹主动段轨迹预报  

Trajectory prediction of boost-phase ballistic missile based on LSTM

作　　者：吉瑞萍[1,2] 张程祎 梁彦 王跃东[1,2] JI Ruiping;ZHANG Chengyi;LIANG Yan;WANG Yuedong(School of Automation,Northwestern Polytechnical University,Xi’an 710072,China;Key Laboratory of Information Fusion Technology,Ministry of Education,Xi’an 710072,China)

机构地区：[1]西北工业大学自动化学院,陕西西安710072 [2]信息融合技术教育部重点实验室,陕西西安710072

出　　处：《系统工程与电子技术》2022年第6期1968-1976,共9页Systems Engineering and Electronics

基　　金：国家自然科学基金(61873205)资助课题。

摘　　要：弹道导弹主动段长周期轨迹预报能够为导弹防御系统提供早期预警信息。传统的轨迹预报方法大多集中在导弹的自由段与再入段,通过解析法、数值积分法或函数逼近法推断未来时刻目标的状态。由于弹道导弹在主动段会受到多个未知作用力的影响,其轨迹预报相比自由段与再入段更具挑战性。为此,本文提出了一种基于长短时记忆(long short-term memeory,LSTM)网络的弹道导弹主动段轨迹预报方法。首先,根据导弹主动段动力学模型与弹道参数典型取值生成用于网络训练的大规模轨迹样本;其次,设计了基于深度LSTM网络的弹道导弹主动段轨迹递归预报方法;最后,与基于数值积分法、多项式拟合及反向传播神经网络的轨迹预报方法的实验对比,表明了所提方法在主动段轨迹预报上的优越性。Long term trajectory prediction for boost-phase ballistic missile(BM)can provide early warning information for the missile defense system.Traditional trajectory prediction methods mostly focus on the BM’s coast and reentry phases,inferring the target state at future time through analytical,numerical integration or function approximation methods.In contrast,the boost-phase trajectory prediction is more challenging because there are many unknown forces acting on the BM during this stage.To this end,a long short-term memory(LSTM)network based boost-phase BM trajectory prediction method is proposed in this paper.Specifically,large-scale trajectory samples for the network training are generated first according to the dynamic model of the boost-phase BM and the typical ballistic parameters.Next,a recursive trajectory prediction method for the boost-phase BM based on deep LSTM network is designed.Finally,simulation results compared with the numerical integration,polynomial fitting and back propagation neural network based trajectory prediction methods show the superiority of the proposed method in long term boost-phase BM trajectory prediction.

关 键 词：弹道导弹 轨迹预报 长短时记忆网络 主动段弹道 

分 类 号：V19[航空宇航科学与技术—人机与环境工程]