TY - GEN
T1 - Intelligent Cooperative Guidance for Multiple Hypersonic Vehicles with Sudden Threat
AU - Ren, Jie
AU - Yu, Jianglong
AU - Dong, Xiwang
AU - Ren, Zhang
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025
Y1 - 2025
N2 - Aiming at the problem of cooperative guidance of multi-vehicles with time coordination under sudden threat, an intelligent cooperative guidance method of multi-vehicles which can evade no-fly zone was proposed. First, taking sudden threat as a circular no-fly zone, a no-fly zone avoidance in transverse trajectory planning is considered. Second, reinforcement learning is introduced into transverse trajectory re-planning, and a fast self-decision making method is proposed. Third, by generating a tilt-angle flip decision maker, multi-vehicles intelligent cooperative guidance for sudden threat is realized. The proposed multi-vehicles intelligent cooperative guidance method not only has a high speed of online trajectory re-planning, but can also greatly improve the penetration probability of sudden threats. The simulation results show the feasibility and effectiveness of the proposed method.
AB - Aiming at the problem of cooperative guidance of multi-vehicles with time coordination under sudden threat, an intelligent cooperative guidance method of multi-vehicles which can evade no-fly zone was proposed. First, taking sudden threat as a circular no-fly zone, a no-fly zone avoidance in transverse trajectory planning is considered. Second, reinforcement learning is introduced into transverse trajectory re-planning, and a fast self-decision making method is proposed. Third, by generating a tilt-angle flip decision maker, multi-vehicles intelligent cooperative guidance for sudden threat is realized. The proposed multi-vehicles intelligent cooperative guidance method not only has a high speed of online trajectory re-planning, but can also greatly improve the penetration probability of sudden threats. The simulation results show the feasibility and effectiveness of the proposed method.
KW - No-fly zones
KW - Online trajectory re-planning
KW - Reinforcement learning
KW - Sudden threat
KW - Tilting angle flip self decision
UR - https://www.scopus.com/pages/publications/105000640735
U2 - 10.1007/978-981-96-2236-8_11
DO - 10.1007/978-981-96-2236-8_11
M3 - 会议稿件
AN - SCOPUS:105000640735
SN - 9789819622351
T3 - Lecture Notes in Electrical Engineering
SP - 106
EP - 116
BT - Advances in Guidance, Navigation and Control - Proceedings of 2024 International Conference on Guidance, Navigation and Control Volume 10
A2 - Yan, Liang
A2 - Duan, Haibin
A2 - Deng, Yimin
PB - Springer Science and Business Media Deutschland GmbH
T2 - International Conference on Guidance, Navigation and Control, ICGNC 2024
Y2 - 9 August 2024 through 11 August 2024
ER -