[1]刘好,刘亚群,谢钧,等.跨域自适应杀伤网研究综述[J].计算机技术与发展,2025,(10):1-9.[doi:10.20165/j.cnki.ISSN1673-629X.2025.0137]
　LIU Hao,LIU Ya-qun,XIE Jun,et al.Comprehensive Survey on Adapting Cross-domain Kill-webs[J].,2025,(10):1-9.[doi:10.20165/j.cnki.ISSN1673-629X.2025.0137]
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跨域自适应杀伤网研究综述()

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2025年10期
页码:
1-9
栏目:
综述
出版日期:
2025-10-10

文章信息/Info

Title:
Comprehensive Survey on Adapting Cross-domain Kill-webs
文章编号:
1673-629X(2025)10-0001-09
作者:
刘好1; 刘亚群2; 谢钧1; 田晨景1
1. 陆军工程大学 指挥控制工程学院,江苏南京 210007;
2. 陆军炮兵防空兵学院无人机应用系,安徽合肥 230031
Author(s):
LIU Hao1; LIU Ya-qun2; XIE Jun1; TIAN Chen-jing1
1. School of Command and Control Engineering,Army Engineering University,Nanjing 210007,China;
2. UAV Application Department,Army Academy of Artillery and Air Defense,Hefei 230031,China
关键词:
跨域自适应杀伤网; 数学模型; 杀伤网构建; 杀伤网调整; 效能评估
Keywords:
Adapting Cross-Domain Kill-Webs (ACK); mathematical model; construction of ACK; adjustment of ACK; effectiveness e-valuation
分类号:
TP391
DOI:
10.20165/j.cnki.ISSN1673-629X.2025.0137
摘要:
随着高强度、高时敏性、高不确定性的跨域作战成为主要形态,传统杀伤链的脆弱性和僵化性日益凸显。为应对这一挑战,快速构建跨域自适应杀伤网(Adapting Cross-Domain Kill-Webs,ACK)在现代战争中对于赢得跨域战争的战场综合控制权具有重要意义。对ACK相关研究进行系统总结形成综述,详细介绍了杀伤网的模型架构,为后续研究奠定了理论基础。在此基础上,从三个关键方面进行了全面梳理和深入分析。首先,在杀伤网构建方面,重点探讨了智能算法与强化学习算法在杀伤网设计中的应用及各类方法的优缺点。随后,在杀伤网调整方面,梳理了当前研究趋势并总结了最新方法与思路。此外,从效能评估的角度提出了指导杀伤网构建评估指标。最后,对未来的研究进行了展望,旨在为相关领域的研究提供参考。
Abstract:
With the increasing prevalence of high-intensity,time-sensitive,and uncertain cross-domain operations,the vulnerability and rigidity of traditional kill chains have become increasingly apparent. To address this challenge,the rapid construction of Adapting Cross-Domain Kill-Webs (ACK) is crucial in modern warfare for achieving comprehensive battlefield control in cross-domain conflicts. To systematically summarize and form a review of ACK-related research,the model architecture of kill-webs is introduced in detail,which lays a theoretical foundation for the subsequent research. Building on this,a comprehensive analysis is conducted from three key perspectives. Firstly,in terms of kill-webs construction,the application of intelligent algorithms and reinforcement learning in kill-webs design is examined,along with the strengths and limitations of various approaches. Secondly,in terms of kill-webs adjustment,current research trends are synthesized,and the latest methods and ideas are summarized. Additionally,from the perspective of effectiveness eval-uation,key metrics for guiding kill-webs construction are proposed. Finally,future research directions are outlined to provide a reference for studies in related fields.

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更新日期/Last Update: 2025-10-10