TY - GEN
T1 - Aircraft Intelligent Guidance Technology for Evasion and Penetration
AU - Li, Jinbai
AU - Wang, Honglun
AU - Liu, Yiheng
AU - Wu, Tiancai
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2022
Y1 - 2022
N2 - In this paper, in order to improve the performance of aircraft evasion and penetration, an intelligent guidance algorithm is proposed by combining twin delayed deep deterministic policy gradient (TD3) and interfered fluid dynamical system (IFDS). First, the guidance model and simulation environment are established. On this basis, the basic guidance algorithm IFDS and the deep reinforcement learning method TD3 are introduced respectively, and the intelligent guidance algorithm is designed. Then, this paper compares and analyzes the simulated flight path of the aircraft obtained by the traditional guidance algorithm and the intelligent guidance algorithm. Finally, simulations show that the intelligent guidance algorithm can guide the aircraft to avoid obstacles and missiles, and demonstrate the advantages of the intelligent guidance algorithm.
AB - In this paper, in order to improve the performance of aircraft evasion and penetration, an intelligent guidance algorithm is proposed by combining twin delayed deep deterministic policy gradient (TD3) and interfered fluid dynamical system (IFDS). First, the guidance model and simulation environment are established. On this basis, the basic guidance algorithm IFDS and the deep reinforcement learning method TD3 are introduced respectively, and the intelligent guidance algorithm is designed. Then, this paper compares and analyzes the simulated flight path of the aircraft obtained by the traditional guidance algorithm and the intelligent guidance algorithm. Finally, simulations show that the intelligent guidance algorithm can guide the aircraft to avoid obstacles and missiles, and demonstrate the advantages of the intelligent guidance algorithm.
KW - Aircraft intelligent avoidance
KW - Deep reinforcement learning
KW - Intelligent guidance algorithm
KW - Interfered fluid dynamical system
UR - https://www.scopus.com/pages/publications/85130919637
U2 - 10.1007/978-981-16-9492-9_189
DO - 10.1007/978-981-16-9492-9_189
M3 - 会议稿件
AN - SCOPUS:85130919637
SN - 9789811694912
T3 - Lecture Notes in Electrical Engineering
SP - 1913
EP - 1922
BT - Proceedings of 2021 International Conference on Autonomous Unmanned Systems, ICAUS 2021
A2 - Wu, Meiping
A2 - Niu, Yifeng
A2 - Gu, Mancang
A2 - Cheng, Jin
PB - Springer Science and Business Media Deutschland GmbH
T2 - International Conference on Autonomous Unmanned Systems, ICAUS 2021
Y2 - 24 September 2021 through 26 September 2021
ER -