TY - CHAP
T1 - A Multi-missile Coverage Interception Strategy
AU - Song, Bao
AU - Yu, Jianqiao
AU - Chen, Xi
AU - Niu, Kang
AU - Li, Ziyuan
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2022
Y1 - 2022
N2 - Due to the error of target indication, the existing laser beam riding guidance weapon system is difficult to intercept the long-range target accurately. In order to solve this problem, a multi-missile coverage interception strategy is proposed in this paper: the total number of missiles determined is decomposed into a finite batch, and the interception probability is improved by adjusting the position of the same group of missiles in the interception plane. In addition, this paper proposes an Improved Grey Wolf Optimizer (IGWO). Based on the traditional Grey Wolf Optimizer, this algorithm generates the initial population uniformly by Hammersley sequence, and adopts a nonlinear convergence factor adjustment method, which can quickly and effectively optimize the location of the missiles. The simulation results show that the improved grey wolf optimizer improves the search accuracy, stability and convergence speed greatly. The multi-missile coverage interception strategy based on the improved grey wolf optimizer can effectively improve the interception accuracy.
AB - Due to the error of target indication, the existing laser beam riding guidance weapon system is difficult to intercept the long-range target accurately. In order to solve this problem, a multi-missile coverage interception strategy is proposed in this paper: the total number of missiles determined is decomposed into a finite batch, and the interception probability is improved by adjusting the position of the same group of missiles in the interception plane. In addition, this paper proposes an Improved Grey Wolf Optimizer (IGWO). Based on the traditional Grey Wolf Optimizer, this algorithm generates the initial population uniformly by Hammersley sequence, and adopts a nonlinear convergence factor adjustment method, which can quickly and effectively optimize the location of the missiles. The simulation results show that the improved grey wolf optimizer improves the search accuracy, stability and convergence speed greatly. The multi-missile coverage interception strategy based on the improved grey wolf optimizer can effectively improve the interception accuracy.
KW - Hammersley sequence
KW - Improved grey wolf optimizer
KW - Multi-missile coverage interception strategy
UR - http://www.scopus.com/inward/record.url?scp=85123445374&partnerID=8YFLogxK
U2 - 10.1007/978-981-16-6640-7_9
DO - 10.1007/978-981-16-6640-7_9
M3 - Chapter
AN - SCOPUS:85123445374
T3 - Springer Aerospace Technology
SP - 105
EP - 118
BT - Springer Aerospace Technology
PB - Springer Science and Business Media Deutschland GmbH
ER -