目标体系分析与选择研究进展

doi:10.12305/j.issn.1001-506X.2025.08.23

系统工程与电子技术 ›› 2025, Vol. 47 ›› Issue (8): 2654-2666.doi: 10.12305/j.issn.1001-506X.2025.08.23

• 系统工程 • 上一篇

目标体系分析与选择研究进展

郑少秋¹(), 陆凌云¹(), 张武¹, 王凯¹^,², 丁炎炎³, 刘凡³, 应励志¹, 陈志新¹^,*

1. 中国电子科技集团公司第二十八研究所，江苏南京 210023
2. 国防科技大学大数据与决策实验室，湖南长沙 410073
3. 河海大学计算机与信息学院，江苏南京 210098

收稿日期:2024-10-16 出版日期:2025-08-25 发布日期:2025-09-04
通讯作者: 陈志新 E-mail:zhengshaoqiu@cetc.com.cn;lulingyun987@163.com
作者简介:郑少秋（1990—），男，研究员，博士，主要研究方向为联合作战筹划、智能指挥控制、深度强化学习
陆凌云（1987—），男，高级工程师，博士，主要研究方向为体系仿真与评估、指控建模、机器学习
张　武（1974—），男，高级工程师，博士，主要研究方向为智能指挥控制
王　凯（1995—），男，工程师，博士，主要研究方向为系统决策建模
丁炎炎（1999—），女，硕士，主要研究方向为机器智能、多模态学习、无人机目标检测
刘　凡（1988—），男，教授，博士，主要研究方向为计算机视觉、模式识别、机器学习
应励志（1987—），男，高级工程师，硕士，主要研究方向为指挥信息系统总体论证设计、大数据挖掘
基金资助:
青年人才托举工程资助课题

Research progress in analysis and selection of target system

Shaoqiu ZHENG¹(), Lingyun LU¹(), Wu ZHANG¹, Kai WANG¹^,², Yanyan DING³, Fan LIU³, Lizhi YING¹, Zhixin CHEN¹^,*

1. The 28th Research Institute of China Electronics Technology Group Corporation，Nanjing 210023，China
2. Laboratory for Big Data and Decision，National University of Defense Technology，Changsha 410073，China
3. College of Computer and Information，Hohai University，Nanjing 210098，China

Received:2024-10-16 Online:2025-08-25 Published:2025-09-04
Contact: Zhixin CHEN E-mail:zhengshaoqiu@cetc.com.cn;lulingyun987@163.com

摘要/Abstract

摘要：

未来战争的战场态势瞬息万变，并向信息域和社会域拓展，目标数量庞大且关系复杂，传统的目标体系分析与选择方法难以满足需求。首先，剖析目标体系分析与选择的相关概念、任务目标、基本原则、影响因素和核心难点。然后，系统梳理六类典型方法的主要思想、计算流程和主要环节，对各方法的优缺点进行比较分析。最后，针对现有方法面临的挑战，提出基于能力的作战任务与目标动态关联、作战任务量化评估、目标关联关系仿真验证等建议，为联合作战筹划系统的发展提供参考。

关键词: 联合目标工作, 目标体系分析, 目标选择, 作战筹划, 联合全域作战

Abstract:

In future warfare, battlefield situations change rapidly and extend into the information and social domains. The number of targets is enormous and their relationships are complex, making traditional methods of target system analysis and selection insufficient to meet demands. This paper first dissects the relevant concepts, mission objectives, basic principles, influencing factors, and core challenges of target system analysis and selection. Then, systematical review is conducted about the main ideas, computational processes, and key steps of six typical methods, providing comparative analysis of their advantages and disadvantages. Finally, in response to the challenges faced by existing methods, suggestions are proposed such as capability-based dynamic association between operational tasks and targets, quantitative evaluation of operational tasks, and simulation verification of target association relationships, offering a reference for the development of joint operational planning systems.

Key words: joint target work, target system analysis, target selection, operational planning, joint all-domain operation

中图分类号:

E 917

郑少秋, 陆凌云, 张武, 王凯, 丁炎炎, 刘凡, 应励志, 陈志新. 目标体系分析与选择研究进展[J]. 系统工程与电子技术, 2025, 47(8): 2654-2666.

Shaoqiu ZHENG, Lingyun LU, Wu ZHANG, Kai WANG, Yanyan DING, Fan LIU, Lizhi YING, Zhixin CHEN. Research progress in analysis and selection of target system[J]. Systems Engineering and Electronics, 2025, 47(8): 2654-2666.

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领域	典型场景	目标特点
火力打击^[16]	火力打击目标选择	目标涉及的影响因素多
火力打击^[17]	岛屿封锁作战炮兵打击目标选择	不同目标具备不同的作用
防御作战^[18]	红方一体化防御对蓝方威胁分析	各目标指数由计算公式表征
作战信息中心侦察^[27]	战场监听目标通信痕迹分析信息中心	不同目标间的关系是通信次数
海上反击^[54]	红蓝对抗，选择升级重要装备，提升对抗能力	不同目标具有不同的能力指标
攻防对抗^[47]	数字化装甲合成营对抗	不同目标具备不同种类功能
网络化协同作战^[51]	确定目标打击顺序和协同方案	选择的目标为不同的打击顺序
攻防对抗^[50]	双方攻防对抗效能分析	分析体系作战效能选择高效损伤方案
体系破击^[53]	联合火力打击目标排序	各节点有属性权重

类型	目标/个		影响因素		筛选要求	方法
类型	组成	规模/个	属性	规模/个	筛选要求	方法
联合火力打击目标体系^[16]	打击目标	8	树状三层影响因素体系	21	到最理想点的距离小则价值优	基于经验价值综合的目标选择方法
网络中心战下常规导弹体系^[26]	导弹打击目标	12	依据上级意图完成任务期望的效果的指标	5	目标链价值大的目标	基于效果的目标选择方法
战术数据链^[27]	通信节点	14	网络体系描述指标	4	体系毁伤效果明显的节点	基于复杂网络分析的目标选择方法
编队对抗体系^[37]	红蓝方目标节点	14	毁伤概率	1	红方节点受损率之和最小	基于解析优化的目标选择方法
装备对抗体系^[54]	侦察、打击、指控装备节点	8	两级能力指标	10	去除某装备后，体系作战环数和作战能力变化率最大的目标	基于复杂网络分析的目标选择方法
网络化协同作战^[51]	指控、侦察预警、打击、防空反导节点	四大系统对应的较多目标	6个个体能力指标和 3个整体能力指标	21	不同数量目标的打击下对体系指标的影响大的方案	基于复杂网络分析的目标选择方法
复杂作战体系^[61]	指控功能节点	50	网络体系描述指标	4	节点重要度排序	基于复杂网络分析的目标选择方法
防御系统^[63]	存在先验概率和成本的目标	15	关于打击决策、运行状态等概率	—	基于影响网络选择压制效果和付出成本合适的目标	基于概率网络的目标选择方法
防御体系^[67]	巡航弹和作战飞机等目标	54	目标价值、攻击次数组成的惩罚指标	2	红方节点受损最小时使用最小的资源	基于深度强化学习的目标选择方法

类型	表示方法	关系类型
指挥体系^[3]	贝叶斯网络（有向无环图）	指控、情报、通信
战术数据链^[27]	加权图	通信
攻防对抗体系^[50]	有向图	进攻、防御
联合火力打击体系^[53]	超网络图	指控、侦察、防空、远火、近火、保障
武器装备体系^[54]	有向环形网络（作战环）	打击
复杂作战体系^[61]	层级网络（具备树形骨架和隐含连接）	指控
防御系统^[63]	影响网络（特殊的贝叶斯网络）	侦察预警、指控、打击、通信等

方法名称	优点	缺点	适用范围
基于经验价值综合的目标选择方法	目标选择结果较客观、可信	目标间关联性考虑不足	目标间关联性弱的场景
基于效果的目标选择方法	可得到明确的目标排序	红蓝博弈考虑不足	多批次多目标饱和攻击等复杂场景
基于解析优化的目标选择方法	简单场景能快速得到解析解	多目标、交互复杂的场景建模困难	小规模、交互关系简单的场景
基于复杂网络分析的目标选择方法	可分析目标在体系中的重要程度	计算复杂度随目标数目增加呈非线性增长	目标数少、作战节奏慢的简单场景
基于概率网络的目标选择方法	可处理目标间不确定性影响关系	需要确定大量条件概率	目标间关联性低的场景
基于深度强化学习的目标选择方法	可快速找出目标节点	模型构建复杂，当目标数量大时训练难度高	复杂强对抗动态作战场景

[1]	高泽伦, 郑少秋, 梁汝鹏, 黄炎焱. 超网络体系作战下的打击目标优选模型[J]. 系统工程与电子技术, 2024, 46(1): 182-189.
[2]	毛琼, 李小民, 王正军. 基于规则的无人机编队队形构建与重构控制方法[J]. 系统工程与电子技术, 2019, 41(5): 1118-1126.

目标体系分析与选择研究进展

Research progress in analysis and selection of target system

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