现代作战任务更加复杂多变,空地导弹的发射条件、作战环境以及目标特征愈加复杂.传统导弹设计依赖于少量离线典型弹道,无法满足现代战争任务的多样化需求,且在线弹道规划无法满足任务快速性,因此迫切需要发展兼顾准确性和快速性的最优弹道生成方法.针对这一问题,提出了一种考虑未知约束空间的空地导弹最优弹道预测方法.构建空地导弹最优弹道预测问题,根据未知约束空间先验未知的特点改进了拉丁超立方采样方法和蒙特卡洛打靶法,提出了基于动态Kriging模型的最优弹道预测流程,针对某空地导弹开展了模型预测准确性与快速性的验证.结果表明:提出方法所预测的中末制导交接点平均弹道倾角误差在0.5°以内,预测时间仅需0.15 s.
Optimal Trajectory Prediction Method for Air-to-ground Missiles Considering Unknown Constraint Space
With the increasing complexity and variability of modern combat tasks,the launch conditions,combat environment,and target characteristics of air-to-ground missiles have become increasingly complex.Traditional missile design relies on a small number of offline typical trajectories,which cannot meet the diverse needs of modern warfare tasks.Online trajectory planning cannot meet the requirements of task speed,so there is an urgent need to develop an optimal trajectory generation method that balances accuracy and speed.This article proposes an optimal trajectory prediction method for air to ground missiles considering unknown constraint spaces.Constructing the optimal trajectory prediction problem for air to ground missiles,the Latin hypercube sampling method and Monte Carlo shooting method are improved based on the characteristics of unknown constraint space prior unknowns.A dynamic Kriging model based optimal trajectory prediction process is proposed,and the accuracy and speed of model prediction are verified for a certain air to ground missile.The results show that the average trajectory inclination angle error predicted by the method proposed in this article at the mid to terminal guidance intersection point is within 0.5°,and the prediction time is only 0.15 s.
Ballistic predictionUnknown constraintDynamic Kriging modelU learning functionSLE-CLHS algorithm
万方数据
维普
