首页 >

面向多战术需求的无人机空战自主规避机动方法

杨振1,李琳2,柴仕元1,黄吉传3,朴海音1,周德云1   

  1. 1. 西北工业大学
    2. 西北工业大学,航 空工业沈阳飞机设计研究所
    3. 西北工业大学,中国人民解放军空军 93147 部队
  • 收稿日期:2024-04-30 修回日期:2024-07-08 出版日期:2024-07-12 发布日期:2024-07-12
  • 通讯作者: 杨振
  • 基金资助:
    国家自然科学基金;航空科学基金;中国博士后科学基金;中央高校基本科研业务费专项资金

For Multiple Tactical Requirements Autonomous Evasive Maneuver Method for Unmanned Combat Aerial Vehicle in Aerial Combat

  • Received:2024-04-30 Revised:2024-07-08 Online:2024-07-12 Published:2024-07-12
  • Contact: Zhen YANG

摘要: 空战通常是一个连续且包含多回合导弹攻防对抗的过程,UCAV(Unmanned Combat Aerial Vehicle)在规避来 袭空空导弹的过程中应该综合考虑机动对整个空战对抗任务的影响,而不是仅仅关注安全性因素。对此,本文提出了脱 靶量、耗能以及终端态势优势等面向多战术需求条件下的UCAV空战自主规避机动策略生成方法。建立了UCAV-导弹三 维空间追逃模型以及UCAV自主规避的状态空间、动作空间和奖励函数模型,针对该模型提出了LSTM-Dueling DDQN (Long Short-Term Memory-Dueling Double Deep Q Network)算法,该算法融合Double DQN(Double Deep Q Network) 和Dueling DQN(Dueling Deep Q Network)网络模型,并使用LSTM网络提取时序特征。此外基于探索课程学习思想, 对稠密与稀疏奖励函数进行时序融合,促进人工经验和策略探索对规避机动学习过程的共同引导。针对战术耦合过程中 的需求冲突问题,构建切比雪夫方法求解面向不同战术需求偏重程度的Pareto策略解集,反映空战机动规避中多种战术 需求的矛盾性与耦合性。仿真实验与结果分析表明,本文所提出的方法具有良好的收敛速度和学习效果,对于解决面向 多战术需求空战自主规避机动问题的可行性与有效性显著,所得出的规避机动方法能够在保证UCAV自身安全性的同时 反应出不同的规避战术需求。

关键词: 空战机动, 自主规避, 战术需求, UCAV, LSTM-Dueling DDQN

Abstract: Unmanned Combat Aerial Vehicle (UCAV) is usually a continuous and multi-round missile attack and defense confrontation process. In the process of evading incoming air-to-air missiles, UCAV should comprehensively consider the impact of maneuvers on the entire air combat confrontation mission, instead of just focusing on security factors. In this paper, the UCAV autonomous evasive maneuver strategy generation method is proposed under the coupling of tactical requirements such as miss distance, energy consumption and terminal situation advantage. The three-dimensional pursuit and escape model of UCAV-missile and the state space, action space and reward function model of UCAV autonomous avoidance are established. LSTM- Dueling DDQN (Long Short-Term Memory-Dueling Double Deep-Q Network) algorithm is proposed for this model. The algorithm fuses Double DQN (Double Deep-Q Network) and Dueling DQN (Dueling Deep-Q Network) network models, and uses LSTM network to extract timing features. Aiming at the demand conflict problem in the local coupling process, the Chebyshev method is constructed to intuitively target the Pareto strategy solution set for different local demand emphasis levels, reflecting the contradiction and coupling of local demands in air combat maneuver avoidance. Simulation experiments and result analysis show that the proposed method has good convergence speed and learning effect, and it is feasible and effective to solve the problem of autonomous evasive maneuvers in air combat for the multiple tactical requirements. The obtained evasive maneuvers can reflect different evasive tactical requirements while ensuring UCAV's own safety.

Key words: Air Combat maneuver, Autonomous Evasive, Tactical Requirements, UCAV, LSTM-Dueling DDQN

中图分类号: