基于改进粒子群优化算法的多弹打击面目标瞄准点优化方法

doi:10.12382/bgxb.2024.0894

摘要/Abstract

摘要：

针对多弹打击复杂形状面目标时的瞄准点优选问题,提出一种改进粒子群优化算法(Improved Particle Swarm Optimization,IPSO)优化多弹最佳瞄准点。构建瞄准点选择模型时,综合考虑面目标区域形状、区域关联、弹药威力区域、弹药命中精度、累积毁伤和多弹联合毁伤等复杂因素对目标毁伤效果的影响。通过预分配粒子位置和引入粒子活化能改进了粒子群优化算法,在提升算法收敛速度的同时又确保了其全局搜索能力,通过典型复杂面目标测试用例验证算法性能。研究结果表明,IPSO算法相比于蒙特卡洛算法、粒子群优化算法和改进灰狼优化算法具有更优的瞄准点选择能力,平均毁伤收益提升4.3%,且平均瞄准点选择耗时仅为其1/4~1/3,在毁伤收益和计算效率上具有明显优势。

关键词: 多弹, 改进粒子群优化算法, 瞄准点选择, 累积毁伤, 联合毁伤, 复杂面目标

Abstract:

An improved particle swarm optimization (IPSO) algorithm is proposed to optimize the optimal aiming point of multiple projectiles against complex-shaped surface targets.When constructing an aiming point selection model,the influences of complex factors such as surface target area shape,regional correlation,ammunition power area,ammunition hit accuracy,cumulative damage and multi-projectiles combined damage on target damage effect are considered comprehensively.Particle swarm optimization (PSO) algorithm is improved by preassigning the particle positions and introducing the particle activation energy,which not only improves the convergence speed of the algorithm but also ensures the global search ability.The proposed algorithm is verified through typical complex target test cases.The results show that,compared with Monte Carlo algorithm,PSO algorithm and improved grey wolf optimization algorithm,the IPSO algorithm has a better ability to select aiming points,and increases the average damage yield by 4.3%.And the average computation time for aiming point selection is only 1/4-1/3 of that of traditional optimization algorithms.,which has obvious advantages in damage income and computing efficiency.

Key words: multiple ammunition, improved particle swarm optimization, aiming point selection, cumulative damage, combined damage, complex surface target

尹鹏, 黄风雷, 石科仁, 严雪飞, 刘彦, 晏江, 俞杰. 基于改进粒子群优化算法的多弹打击面目标瞄准点优化方法[J]. 兵工学报, 2025, 46(9): 240894-.

YIN Peng, HUANG Fenglei, SHI Keren, YAN Xuefei, LIU Yan, YAN Jiang, YU Jie. An Improved Particle Swarm Optimization Algorithm for Optimizing the Aiming Point of Multiple Projectiles against Surface Targets[J]. Acta Armamentarii, 2025, 46(9): 240894-.

图/表 11

表1 使用弹药的威力区域

Table 1 The power area of the ammunition used

弹药类型	威力区域	描述	CEP/m
1		直径为12m的圆形	6
2		长轴为20m、短轴为12m 的椭圆形	12

图1 弹药落点概率矩阵

Fig.1 Ammunition landing probability matrix

图2 典型面目标区域分布和区域编号

Fig.2 Typical surface target area distribution and area number

表2 目标区域毁伤相关系数和关联列表

Table 2 Correlation coefficient and correlation list of damage in target area

编号	I_c	I_a	D_c	D_a	C_l
1	0.05	0.10	0.02	0.10
2	0.50	0.30	0.60	0.20
3	0.70	0.25	0.50	0.15	(1,0.32)
4	0.70	0.25	0.50	0.14	(1,0.32)
5	0.65	0.30	0.70	0.30	(12,0.50)
6	0.75	0.35	0.80	0.33	(4,0.45)
7	0.75	0.34	0.80	0.34	(4,0.44)
8	0.62	0.35	0.71	0.23	(8,0.25)
9	0.66	0.45	0.69	0.19
10	0.66	0.45	0.69	0.19
11	0.80	0.35	0.77	0.31	(8,0.25),(11,0.35)
12	0.81	0.25	0.59	0.43
13	0.84	0.25	0.59	0.43
14	0.92	0.44	0.70	0.47	(12,0.30),(14,0.28),(11,0.15)
15	0.52	0.25	0.59	0.43	(11,0.32)
16	0.79	0.44	0.57	0.47	(17,0.30)
17	0.71	0.41	0.59	0.45
18	0.66	0.35	0.64	0.30

图3 算法毁伤收益与求解时间

Fig.3 Damage yield and solution time

图4 4种算法的瞄准点选择结果

Fig.4 Aiming point selection results of 4 algorithms

图5 3种算法的目标函数典型收敛曲线

Fig.5 Typical convergence curves of objective functions of three algorithms

图6 不同用弹量下的毁伤收益和求解时间

Fig.6 Damage yield and solution time at different levels of projectile usage

表3 调整目标区域

Table 3 Adjusting target area

编号	I_c	I_a	D_c	D_a	C_l
1	0.05	0.10	0.02	0.10
2	0.50	0.30	0.60	0.20
3	0.70	0.25	0.50	0.15	(1,0.32)
4	0.70	0.25	0.50	0.14
5	0.65	0.30	0.70	0.30
6	0.75	0.35	0.80	0.33
7	0.75	0.34	0.80	0.34
8	0.62	0.35	0.71	0.23	(8,0.25),(9,0.35)
9	0.66	0.45	0.69	0.19
10	0.66	0.45	0.69	0.19
11	0.80	0.35	0.77	0.31
12	0.81	0.25	0.59	0.43
13	0.84	0.25	0.59	0.43
14	0.92	0.44	0.70	0.47	(12,0.40),(14,0.28)
15	0.52	0.25	0.59	0.43
16	0.79	0.44	0.57	0.47
17	0.71	0.41	0.59	0.45	(17,0.25)
18	0.66	0.35	0.64	0.30

图7 新目标下4种算法的瞄准点选择结果

Fig.7 Aiming point selection results of 4 algorithms in the case of new target

图8 新目标下不同用弹量下的毁伤收益和求解时间

Fig.8 Damage yield and solution time at different levels of projectile usage for new target

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