Electronics Optics & Control, Volume. 30, Issue 1, 8(2023)

An Autonomous Guidance Method of UAV in Close Air Combat Based on PPO Algorithm

QIU Yan1,2, ZHAO Baoqi3, ZOU Jie1,2, and LIU Zhongkai1,2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
  • show less

    Aiming at the problem of UAVs autonomous decision-making in close air combat, an autonomous guidance method for UAV based on Proximal Policy Optimization (PPO) algorithm is proposed.The rewards are reshaped, such as distance, angle, speed and mission constraint, a three-degree-of-freedom model of UAV is established, and the state and action of reinforcement learning are constructed on the velocity coordinate system.The simulation training is carried out on the model of PPO algorithm combined with the fully connected neural network(standard PPO algorithm) and the PPO algorithm combined with the long short-term memory network (improved PPO algorithm) respecitively.According to the training results, it can be proved that, compared with the standard PPO algorithm, the improved PPO algorithm proposed in this paper can handle the UAV autonomous guidance tasks that are highly correlated with time series more effectively.

    Tools

    Get Citation

    Copy Citation Text

    QIU Yan, ZHAO Baoqi, ZOU Jie, LIU Zhongkai. An Autonomous Guidance Method of UAV in Close Air Combat Based on PPO Algorithm[J]. Electronics Optics & Control, 2023, 30(1): 8

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category:

    Received: Jul. 19, 2022

    Accepted: --

    Published Online: Apr. 3, 2023

    The Author Email:

    DOI:10.3969/j.issn.1671-637x.2023.01.002

    Topics