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带防御器的超高速飞行器智能协同博弈方法(航天运输系统自主制导与控制专栏)

郭容義,丁一波,岳晓奎   

  1. 西北工业大学
  • 收稿日期:2025-10-23 修回日期:2025-12-28 出版日期:2025-12-29 发布日期:2025-12-29
  • 通讯作者: 丁一波
  • 基金资助:
    国家自然科学基金;中国科学技术协会青年人才托举工程;航空科学基金资助项目;中国博士后科学基金资助项目

Intelligent collaborative game method for high-speed vehicle with defender

Rongyi Guo1,Yi-bo DING2,   

  • Received:2025-10-23 Revised:2025-12-28 Online:2025-12-29 Published:2025-12-29
  • Contact: Yi-bo DING

摘要: 针对超高速飞行器通过携带防御器主动打击来袭攻击器保护自身安全的三体博弈机动策略求取问题,设计了基于深度确定性策略梯度的智能协同博弈制导方法。首先,为防御器设计了一种时变幂次固定时间制导律,可基于视线角速度收敛状况实时自主调节分数阶幂次,实现视线角速度固定时间收敛。然后,设计了基于深度确定性策略梯度的超高速飞行器诱导机动制导律,通过超高速飞行器诱导性机动,引诱攻击器机动至防御器可打击区域,最小化防御器打击攻击器脱靶量,并显著减小机动消耗。基于上述固定时间制导律与诱导机动制导律,得到智能协同博弈制导方法,确保了防御器弱机动能力下对强机动攻击器的高博弈胜率。最后,开展仿真测试以验证智能协同博弈制导方法的有效性与泛化能力,仿真结果表明超高速飞行器与防御器获胜概率超过90%。

关键词: 超高速飞行器, 主动防御, 时变幂次固定时间制导律, 深度确定性策略梯度

Abstract: An intelligent collaborative game guidance method based on deep deterministic strategy gradient is designed to deal with the three-body game problem of high-speed vehicle actively using defender to hit incoming attacker and protect its safety. Firstly, a variable-exponent fixed-time guidance law is designed for the defender, which can autonomously adjust the exponent in real-time based on the convergence status of the line-of sight angle rate to accelerate convergence time, and ensure that the line-of-sight angle rate converges to zero with fixed time. Then, a lure maneuvering guidance law based on deep determinis-tic policy gradient for high-speed vehicle is designed. By applying this lure maneuvering guidance law, the high-speed vehi-cle can lure attacker to maneuver to areas that are convenient for defender to hit attacker, which can minimize miss distance of defender, and significantly reduce required maneuverability of high-speed vehicle and defender. Based on the fixed time guidance law and lure maneuvering guidance law mentioned, an intelligent collaborative game guidance method is obtained. Through the coordinated movement of high-speed vehicle and defender, the weakly maneuvering defender can successfully strike the strongly maneuvering attacker with a high probability. Finally, simulations are carried out to verify the effectiveness and strong generalization ability of the designed intelligent collaborative game guidance method based on deep deterministic policy gradients. The simulation results demonstrate that under different game situations, the winning probability exceeds 90% for the high-speed vehicle and defender.

Key words: high-speed vehicle, active defend, variable-exponent fixed-time guidance law, deep deterministic policy gradient

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