基于深度强化学习的来袭导弹智能拦截与平台机动策略优化技术  

Optimization Technology for Intelligent Interception of Incoming Missiles and Platform Maneuvering Strategies Based on Deep Reinforcement Learning

作　　者：吕振瑞 沈欣 李少博 田鹏[1,2] 司迎利 LüZhenrui;Shen Xin;Li Shaobo;Tian Peng;Si Yingli(China Airborne Missile Academy,Luoyang 471009,China;National Key Laboratory of Air-based Information Perception and Fusion,Luoyang 471009,China;The First Military Representative Office of Air Force Equipment Department in Luoyang,Luoyang 471009,China;Xi’an Jiaotong University,Xi’an 710049,China)

机构地区：[1]中国空空导弹研究院,河南洛阳471009 [2]空基信息感知与融合全国重点实验室,河南洛阳471009 [3]空装驻洛阳地区第一军事代表室,河南洛阳471009 [4]西安交通大学,西安710049

出　　处：《航空兵器》2024年第5期56-66,共11页Aero Weaponry

摘　　要：目前空中作战环境日益复杂,新作战方式对空中平台生存能力提出了巨大挑战,需要采用新型硬杀伤手段来防御先进的空空导弹。为了提升发射空空导弹拦截来袭导弹这一硬杀伤手段的胜率和效率,提出了一种基于强化学习的载机平台智能机动策略和拦截弹发射策略。首先,设计了导弹威胁评估技术,构建了仿真环境,并确定了策略模型的状态和奖励函数;其次,通过设定不同的来袭空空导弹攻击角度和位置,在不同载机平台姿态下,训练了机动与拦截策略,实现了对来袭目标的主动拦截和载机平台的有效机动。实验表明,相较于运筹学博弈策略5.8%的平均逃离概率,使用基于强化学习的机动、拦截策略后,逃离概率可提升至56.8%;同时,拦截弹利用率提高了约13.3%,且响应时间始终保持在24 ms以内。设计的策略能够自适应不同数量的来袭导弹,显著提高了载机平台的生存能力和对来袭导弹的拦截成功率,并支持在空战多维状态空间中的持续优化。Facing the increasing complexity of aerial combat environments and challenges to the survivability of air platforms from new combat methods,it is necessary to adopt new hard-kill methods to counter advanced air-to-air missiles.In order to improve the success rate and efficiency of launching air-to-air missiles to intercept incoming missiles as a hard kill method,this study proposes intelligent maneuvering strategies for aircraft platforms and missile interception strategies based on reinforcement learning.Firstly,this paper designs the missile threat assessment technology,constructs the simulation environments,and determines the strategy model state and reward function.By setting various attack angles and positions of incoming air-to-air missiles and training maneuvering and intelligent interception strategies under different aircraft platform postures,this paper achieves active interception of incoming targets and effective maneuvering of the aircraft platform.Experiments show that compared to the average escape probability of 5.8%in operations research game strategies,after using maneuver and interception strategies based on reinforcement learning,the average escape probability can increase to 56.8%;Meanwhile,the utilization rate of interceptors has increased by approximately 13.3%,and the response time has remained within 24 ms.The designed strategy can adapt to different numbers of incoming missiles,can significantly improve the survival ability of the carrier platform and the success rate of intercepting incoming missiles.This study can support continuous optimization in a high-dimensional state space of air combat.

关 键 词：拦截弹 机动策略 强化学习 拦截策略 逃离概率 响应时间 空空导弹 

分 类 号：TJ760[兵器科学与技术—武器系统与运用工程]