Trajectory prediction of ballistic missiles using Gaussian process error model

作     者：Ruiping JI Yan LIANG Linfeng XU Zhenwei WEI Ruiping JI;Yan LIANG;Linfeng XU;Zhenwei WEI

作者机构：School of AutomationNorthwestern Polytcchnical UniversityXi'an 710129China Key Laboratory of Information Fusion TechnologyMinistry of EducationXi'an 710129China 

出 版 物：《Chinese Journal of Aeronautics》 (中国航空学报（英文版）)

年 卷 期：2022年第35卷第1期

页      面：458-469页

核心收录：

学科分类：082601[工学-武器系统与运用工程] 08[工学] 082501[工学-飞行器设计] 0826[工学-兵器科学与技术] 082602[工学-兵器发射理论与技术] 0825[工学-航空宇航科学与技术] 

基　　金：support from National Natural Science Foundation of China(Nos.61873205,61771399) Aerospace Science Foundation of China(No.2019-HT-XGD) Natural Science Basic Research Plan in Shaanxi Province of China(No.2020JM-101) 

主　　题：Ballistic missile Boost-phase trajectory State prediction Gaussian processes Uncertainty estimation 

摘      要：Ballistic Missile Trajectory Prediction(BMTP)is critical to air defense *** Trajectory Prediction(TP)methods focus on the coast and reentry phases,in which the Ballistic Missile(BM)trajectories are modeled as ellipses or the state components are propagated by the dynamic integral equations on time *** contrast,the boost-phase TP is more challenging because there are many unknown forces acting on the BM in this *** tackle this difficult problem,a novel BMTP method by using Gaussian Processes(GPs)is proposed in this *** particular,the GP is employed to train the prediction error model of the boost-phase trajectory database,in which the error refers to the difference between the true BM state at the prediction moment and the integral extrapolation of the BM *** the final BMTP is a combination of the dynamic equation based numerical integration and the GP-based prediction *** the trained GP aims to capture the relationship between the numerical integration and the unknown error,the modified BM state prediction is closer to the true one compared with the original ***,the GP is able to output the uncertainty information of the TP,which is of great significance for determining the warning range centered on the predicted BM *** results show that the proposed method effectively improves the BMTP accuracy during the boost phase and provides reliable uncertainty estimation boundaries.