TY - GEN
T1 - Weapon Target Assignment Method with Grouping Constraints for Interception Based on Artificial Bee Colony Algorithm∗
AU - Guo, Dong
AU - Dong, Xiwang
AU - Li, Qingdong
AU - Ren, Zhang
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - This paper presents a weapon-target assignment (WTA) method for multi-to-multi interception with grouping constraints based on penalty function method. Firstly, in order to evaluate the combat performance from the interception efficiency and the required energy, the interception probability function are constructed of the heading error, the time-to-go for moving targets and the line-of-sight rate. Secondly, to ensure that each target is allocated with sufficient interception resources, and meanwhile to achieve the effective interception for multiple missiles against multiple targets, an adaptive grouping strategy is presented. Then, based on the artificial bee colony algorithm, the steps for solving WTA problem with grouping constraints are given. Finally, the proposed WTA method is verified with numerical simulations. Results indicate that the proposed WTA methods can realize the optimal allocation scheme which satisfying adaptive grouping constraints.
AB - This paper presents a weapon-target assignment (WTA) method for multi-to-multi interception with grouping constraints based on penalty function method. Firstly, in order to evaluate the combat performance from the interception efficiency and the required energy, the interception probability function are constructed of the heading error, the time-to-go for moving targets and the line-of-sight rate. Secondly, to ensure that each target is allocated with sufficient interception resources, and meanwhile to achieve the effective interception for multiple missiles against multiple targets, an adaptive grouping strategy is presented. Then, based on the artificial bee colony algorithm, the steps for solving WTA problem with grouping constraints are given. Finally, the proposed WTA method is verified with numerical simulations. Results indicate that the proposed WTA methods can realize the optimal allocation scheme which satisfying adaptive grouping constraints.
UR - https://www.scopus.com/pages/publications/85075782443
U2 - 10.1109/ICCA.2019.8899559
DO - 10.1109/ICCA.2019.8899559
M3 - 会议稿件
AN - SCOPUS:85075782443
T3 - IEEE International Conference on Control and Automation, ICCA
SP - 1385
EP - 1390
BT - 2019 IEEE 15th International Conference on Control and Automation, ICCA 2019
PB - IEEE Computer Society
T2 - 15th IEEE International Conference on Control and Automation, ICCA 2019
Y2 - 16 July 2019 through 19 July 2019
ER -