高炮弹药抗击“低小慢”无人机及其蜂群毁伤评估快速算法

孙泽瑞; 郑海文; 王风华; 雷亚猛; 赵耀; 李洪

doi:10.12382/bgxb.2025.0723

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高炮弹药抗击“低小慢”无人机及其蜂群毁伤评估快速算法

更新时间：2026-02-10

- 高炮弹药抗击“低小慢”无人机及其蜂群毁伤评估快速算法
- A Rapid Algorithm for Damage Assessment of Antiaircraft Ammunitions Countering Low, Slow and Small UAVs and Their Swarms
- 兵工学报 2025年46卷第S2期页码：250723
- 作者机构：
  
  1. 陆军兵种大学, 河南郑州 450052
  2. 重庆长安工业(集团)有限责任公司, 重庆 401120
- 作者简介：
  
  * 邮箱: optimist07@163.com
- 基金信息：
- DOI：10.12382/bgxb.2025.0723
  中图分类号：
- 收稿：2025-07-23，
  
  网络首发：2026-02-03，
  
  纸质出版：2025
- 稿件说明：
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孙泽瑞, 郑海文, 王风华, 等. 高炮弹药抗击“低小慢”无人机及其蜂群毁伤评估快速算法[J]. 兵工学报, 2025,46(S2):250723.

Zerui SUN, Haiwen ZHENG, Fenghua WANG, et al. A Rapid Algorithm for Damage Assessment of Antiaircraft Ammunitions Countering Low, Slow and Small UAVs and Their Swarms[J]. Acta Armamentarii, 2025, 46(S2): 250723.
孙泽瑞, 郑海文, 王风华, 等. 高炮弹药抗击“低小慢”无人机及其蜂群毁伤评估快速算法[J]. 兵工学报, 2025,46(S2):250723. DOI： 10.12382/bgxb.2025.0723.

Zerui SUN, Haiwen ZHENG, Fenghua WANG, et al. A Rapid Algorithm for Damage Assessment of Antiaircraft Ammunitions Countering Low, Slow and Small UAVs and Their Swarms[J]. Acta Armamentarii, 2025, 46(S2): 250723. DOI： 10.12382/bgxb.2025.0723.

摘要

针对“低小慢”无人机及其蜂群对末端防空构成的现实威胁

聚焦高炮弹药抗击该类目标的毁伤评估快速算法。通过有限元仿真构建弹药破片威力场

结合静爆试验验证破片参数准确性;二次开发构建某型四旋翼无人机部件级易损性模型

实现几何特征自动化提取;通过弹道解算与坐标系转换确定弹目交会姿态

融合射击线法与蒙特卡洛模拟完成单发弹药毁伤概率计算。在此基础上探索无人机蜂群抗击策略

单弹场景下结合蜂群投影位置与毁伤概率分布优化瞄点选择

多弹场景下引入

-Means算法对蜂群分簇

以确定最优多瞄点配置。研究结果表明:无人机毁伤概率峰值并非随距离缩短单调递增

而是与距高组合导致的破片飞散角及弹道倾角相关;确定最佳瞄点时应以弹目交会的脱靶平面为基准

而脱靶平面的空间姿态又受目标高度与距离的直接影响;基于Python与TTK开发的毁伤评估软件引入多线程技术提升计算效率

可为反无人机作战提供毁伤效能评估与瞄点决策支持

从而填补高炮弹药在反无人机及其蜂群上的空白。

Abstract

In response to the practical threat posed by the low

slow and small unmanned aerial vehicles (LSS UAVs) and their swarms to terminal air defense

this paper focuses on a rapid algorithm for the damage assessment of antiaircraft ammunitions countering LSS UAVs.The fragment power field of the ammunition is constructed through finite element simulation

and the accuracy of fragment parameters is verified through static explosion tests.Based on the secondary development

a component-level vulnerability model for a certain type of quadrotor UAV is built to realize the automatic extraction of geometric features.The projectile-target intersection attitude is determined through ballistic calculation and coordinate system conversion

and the damage probability of single-round ammunition is calculated by integrating the shotline method and Monte Carlo simulation.On this basis

the strategies for countering UAV swarms are explored.In single-ammunition scenarios

The selection of aiming points is optimized

by combining the projected position of UAV swarm and the distribution of damage probability

and in multi-ammunition scenarios

the

-Means algorithm is introduced to cluster the UAV swarm to determine the optimal multi-aiming point configuration.The results shows that the peak damage probability of UAVs does not increase monotonically as the distance decreases

but it is related to the dispersion angle of fragments and the ballistic inclination caused by the combination of distance and height.The optimal aiming point should be determined based on the miss distance plane of projectile-target intersection

and the spatial attitude of the miss distance plane is directly affected by the target’s height and distance.Finally

the damage assessment software developed based on Python and TTK incorporates multi-threading technology to improve the computational efficiency

which can provide support for damage effectiveness assessment and aiming point decision-making in anti-UAV operations

thereby filling the gap in antiaircraft artillery ammunition for countering UAVs and their swarms.

关键词

Keywords

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