基于改进灰狼算法的多弹种瞄准点选择方法

doi:10.12305/j.issn.1001-506X.2025.05.22

摘要/Abstract

摘要：

目前, 远程多管火箭炮可携带的弹药类型逐渐多样, 这为弹药瞄准点的寻优选取问题带来新的挑战。针对以往算法在复杂瞄准点寻优模型中求解速度较慢、求解质量较差的问题, 提出一种改进的灰狼算法, 通过融合多层多模块编码策略、自适应变异和模拟退火策略以及单一决策个体交叉引导策略, 提升算法的寻优能力和求解速度。实验结果表明, 相较于对比算法, 所提算法在红蓝双方作战力量发生变化时, 能够保持更快的求解速度, 选择出的瞄准点综合毁伤效果更优, 具有一定的应用价值。

关键词: 弹药, 瞄准点, 灰狼算法, 目标毁伤

Abstract:

At present, the types of munitions that can be carried by long-range multiple-launch rockets are becoming more and more diversified, which brings new challenges to the problem of optimization of munition aiming points. Aiming at the problems of previous algorithms' slow solution speed and poor solution quality in complex aiming point optimization models, this paper proposes an improved gray wolf algorithm, which enhances the algorithm's optimization ability and solution speed by incorporating a multi-layer multi-module coding strategy, adaptive mutation and simulated annealing strategy, and a single-decision-individual cross-guidance strategy. The experimental results show that, compared with the comparison algorithm, the algorithm proposed in this paper can maintain a faster solution speed when the combat forces of the red and blue sides change, and the comprehensive destructive effect of the selected aiming point is better, which has certain application value.

Key words: ammunition, point of aim, gray wolf algorithm, target destruction

中图分类号:

TN911

赵拓, 付仲豪, 王东喜, 张正辉, 马远. 基于改进灰狼算法的多弹种瞄准点选择方法[J]. 系统工程与电子技术, 2025, 47(5): 1609-1619.

Tuo ZHAO, Zhonghao FU, Dongxi WANG, Zhenghui ZHANG, Yuan MA. Multi-magazine aiming point selection method based on improved gray wolf algorithm[J]. Systems Engineering and Electronics, 2025, 47(5): 1609-1619.

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编号	坐标位置/m	编号	坐标位置/m
5	(130, 130)	10	(440, 310)
6	(115, 130)	11	(560, 570)
7	(120, 135)	12	(445, 310)
8	(100, 125)	13	(460, 320)
9	(440, 290)	14	(100, 560)

算法	耗时/s
MAGA	7.8
MSPSO	12.6
GWO	20.3
ISA-GWO	4.3

算法	毁伤收益
MAGA	0.977
MSPSO	1.155
GWO	1.568
ISA-GWO	2.843

算法	侵爆弹	子母弹	杀爆弹	云爆弹
MAGA	(335, 511)	(45, 489)	(557, 553)	(234, 290)
MSPSO	(244, 592)	(152, 490)	(330, 273)	(142, 144)
GWO	(302, 207)	(355, 256)	(453, 304)	(181, 323)
ISA-GWO	(88, 497)	(85, 493)	(459, 306)	(254, 192)

算法	耗时/s
MAGA	30.8
MSPSO	52.2
GWO	90.0
ISA-GWO	15.7