异构无人集群杀伤网任务路径生成建模与评估

doi:10.12305/j.issn.1001-506X.2025.10.15

摘要/Abstract

摘要：

针对异构无人集群杀伤网任务路径生成建模整体统筹不足和评估关联分析薄弱的问题，提出一种基于多层网络与数据包络分析（data envelopment analysis，DEA）的任务路径生成建模与评估方法。一是构建“目标-线程-兵力”3层网络模型，提出融合目标优先级与闭合任务路径转化率，量化任务路径可用性；二是设计约束传播与回溯搜索算法，通过功能、结构、行为关联性约束剪枝，实现闭合任务路径的高效检索；三是基于DEA构建兵力关联性评估模型，揭示功能冗余、行为冗余与结构不足对任务路径生成效率的影响机制。实验验证表明，约束传播与回溯搜索算法较全组合枚举法效率提升显著，DEA为兵力配置优化提供了量化依据。研究成果可为HUS-KW的体系建模与能力提升提供理论支撑。

关键词: 任务工程, 异构无人集群, 杀伤网, 杀伤链, 数据包络分析

Abstract:

To address the problems in insufficient overall coordination and week evaluation correlation analysis for mission path generation modeling in heterogeneous unmanned swarm kill-web, a mission path generation modeling and evaluation method based on multi-layer network and data envelopment analysis （DEA） is proposed. Firstly, a three-layer network model （“target-thread-force”） is constructed, combining target prioritization and effective path conversion rate to assess mission path availability. Secondly, a constraint propagation and backtracking search algorithm is proposed, leveraging functional, structural, and behavioral correlation constraints prune to achieve efficient retrieval of closed task paths. Thirdly, a DEA-based force correlation evaluation model is constructed to quantify the impact of functional redundancy, behavioral redundancy, and structural deficiencies on path generation efficiency. Experimental results demonstrate that constraint propagation and backtracking search algorithm significantly outperforms full combinatorial enumeration in computational efficiency, while DEA provides quantitative basis for force allocation optimization. The findings can provide theoretical foundations for HUS-KW system modeling and capability enhancement.

Key words: mission engineering, heterogeneous unmanned swarm （HUS）, kill web, kill chain, data envelopment analysis （DEA）

中图分类号:

E 917

杨松, 王涛, 李小波, 何华, 孙吉东. 异构无人集群杀伤网任务路径生成建模与评估[J]. 系统工程与电子技术, 2025, 47(10): 3278-3287.

Song YANG, Tao WANG, Xiaobo LI, Hua HE, Jidong SUN. Modeling and evaluation of mission path generation in heterogeneous unmanned swarm kill-web[J]. Systems Engineering and Electronics, 2025, 47(10): 3278-3287.

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