Aiming at the coordination between maneuvering penetration and high-precision guidance under complex flight missions of high-velocity vehicle, the manuscript studies a three-dimensional high-dynamic intelligent maneuvering guidance strategy based on optimal control and deep reinforcement learning (DRL). A three-dimensional attack–defense model is established, and maneuver guidance mission is decomposed into longitudinal and lateral directions. In the longitudinal direction, maneuvering model with the instantaneous miss distance as the control variable is constructed, and the maximum value principle is employed to obtain the optimal maneuver duration and start timing. In the lateral direction, Markov decision process model of maneuver guidance is proposed by synthesizing the guidance error and miss distance of encounter point, and the reward function is designed by considering maneuver and guidance performance. The DRL method is used to learn and train the maneuver strategy, and the training process is improved as well. The simulation results show that the intelligent maneuvering guidance strategy can improve the penetration performance, reduce influence of maneuver flight on the guidance accuracy, and ensure the adaptability under changeable flight missions.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    High-dynamic intelligent maneuvering guidance strategy via deep reinforcement learning


    Contributors:
    Zhao, Sibo (author) / Zhu, Jianwen (author) / Bao, Weimin (author) / Li, Xiaoping (author)


    Publication date :

    2023-09-01


    Size :

    15 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Intercept Guidance of Maneuvering Targets with Deep Reinforcement Learning

    Zhe Hu / Liang Xiao / Jun Guan et al. | DOAJ | 2023

    Free access

    A Multi-Constraint Guidance and Maneuvering Penetration Strategy via Meta Deep Reinforcement Learning

    Sibo Zhao / Jianwen Zhu / Weimin Bao et al. | DOAJ | 2023

    Free access

    Deep reinforcement learning guidance law for intercepting random maneuvering target spacecraft

    YE DONG / JIANG RUI / XIAO YAN et al. | European Patent Office | 2024

    Free access


    Dynamic Programming Guidance Law for Maneuvering Target

    Yang, Xiuxia / Jiang, Zijie / Zhang, Yi et al. | Springer Verlag | 2022