TY - GEN
T1 - Formation Optimization Method of Multiple Hypersonic Vehicles
AU - Zhang, Yuqing
AU - Yu, Jianglong
AU - Dong, Xiwang
AU - Li, Qingdong
AU - Ren, Zhang
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2023
Y1 - 2023
N2 - This paper constructed a collaborative combat effectiveness evaluation system with considering the characteristics and limitations of the vehicles. Firstly, multiple hypersonic vehicles formation problem is converted to an optimization problem based on the collaborative combat effectiveness evaluation system. Secondly, the relative distance and angles between vehicle and a certain reference point is selected as the formation parameters, which are chosen as optimization variables in the optimization algorithm. Thirdly, the efficiency function corresponding to each evaluation indicator is given under the constraints of the vehicle and the PSACO (particle swarm ant colony optimization) algorithm is used to solving this optimization problem. In particular, the scenario of detection and the scenario of penetration are designed respectively considering different combat requirements. Finally, it can be verified that multiple hypersonic vehicles can achieve cooperative optimal formation in two combat scenarios through the effectiveness evaluation system and the PSACO algorithm according to simulation examples.
AB - This paper constructed a collaborative combat effectiveness evaluation system with considering the characteristics and limitations of the vehicles. Firstly, multiple hypersonic vehicles formation problem is converted to an optimization problem based on the collaborative combat effectiveness evaluation system. Secondly, the relative distance and angles between vehicle and a certain reference point is selected as the formation parameters, which are chosen as optimization variables in the optimization algorithm. Thirdly, the efficiency function corresponding to each evaluation indicator is given under the constraints of the vehicle and the PSACO (particle swarm ant colony optimization) algorithm is used to solving this optimization problem. In particular, the scenario of detection and the scenario of penetration are designed respectively considering different combat requirements. Finally, it can be verified that multiple hypersonic vehicles can achieve cooperative optimal formation in two combat scenarios through the effectiveness evaluation system and the PSACO algorithm according to simulation examples.
KW - Effectiveness evaluation system
KW - Formation optimization
KW - Multiple hypersonic vehicles
KW - The PSACO algorithm
UR - https://www.scopus.com/pages/publications/85151117805
U2 - 10.1007/978-981-19-6613-2_456
DO - 10.1007/978-981-19-6613-2_456
M3 - 会议稿件
AN - SCOPUS:85151117805
SN - 9789811966125
T3 - Lecture Notes in Electrical Engineering
SP - 4702
EP - 4712
BT - Advances in Guidance, Navigation and Control - Proceedings of 2022 International Conference on Guidance, Navigation and Control
A2 - Yan, Liang
A2 - Duan, Haibin
A2 - Deng, Yimin
A2 - Yan, Liang
PB - Springer Science and Business Media Deutschland GmbH
T2 - International Conference on Guidance, Navigation and Control, ICGNC 2022
Y2 - 5 August 2022 through 7 August 2022
ER -