Development of Combat Concept of Intelligent Land Assault System Based on DoDAF

doi:10.16182/j.issn1004731x.joss.22-0628

Abstract

Abstract:

In view of military demand traction in the development of land assault equipment, a combat concept of land assault systems for future intelligent combat is developed. Basedon the definition of relevant concepts and research boundaries, the combat concept model framework and modeling steps are proposed based on DoDAF, and the combat effect, combat process, combat nodes, resource interaction, system composition, and capability characteristics are analyzed in combination with the model description. The combat concept verification is carried out from the aspects of system combat efficiency and communication load by simulation experiments. The results show that the intelligent assault system has more agile strike links and stronger firepower strike capability than the traditional assault equipment, and the new communication load pressure is within the current technical capacity support range. It proves that the selection, allocation, and combat mode of the core executor system in the combat concept are reasonable and feasible, which has reference significance for the subsequent development of equipment.

Key words: DoDAF, land combat, intelligent, assault system, combat concept, modeling and simulation

CLC Number:

TP391.9

Wang Can, Ji Haoran, Guo Qisheng, Dong Zhiming, Tan Yaxin, Mu Ge. Development of Combat Concept of Intelligent Land Assault System Based on DoDAF[J]. Journal of System Simulation, 2023, 35(11): 2397-2409.

Figures/Tables 14

Table 1

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Table 2

Fig. 5

Fig. 6

Fig. 7

Table 3

Table 4

Fig. 8

Fig. 9

Fig. 10

References 16

1	胡晓峰. 战争工程论-走向信息时代的战争方法学(修订版)[M]. 北京: 科学出版社, 2017.
2	龚旻, 卜昭鹏, 陈梅, 等. 陆战分队空地一体无人作战系统装备体系构想研究[J]. 无人系统技术, 2021, 4(1): 71-78.
	Gong Min, Bu Zhaopeng, Chen Mei, et al. Construction Strategy Study on Air-ground Unmanned Operation System for Land Combat Units[J]. Unmanned Systems Technology, 2021, 4(1): 71-78.
3	姚红霞. 美陆军无人系统发展规划及建设情况研究[J]. 现代军事, 2017(9): 86-91.
4	张宇. 地面无人作战系统作战效能试验评估研究[D]. 北京: 陆军装甲兵学院, 2020.
	Zhang Yu. Research on Operational Effectiveness Test Evaluation of Ground Unmanned Combat System[D]. Beijing: Army Armored Force Academy, 2020.
5	张宇, 郭齐胜. 基于DoDAF的地面无人作战系统作战概念设计方法[J]. 火力与指挥控制, 2021, 46(5): 52-57, 63.
	Zhang Yu, Guo Qisheng. Operational Concept Design Method Based on DoDAF for Ground Unmanned Combat System[J]. Fire Control & Command Control, 2021, 46(5): 52-57, 63.
6	周菁, 杨鸣坤, 王磊, 等. 基于DoDAF的有/无人协同特战系统总体结构设计[J]. 兵工自动化, 2021, 40(1): 3-7.
	Zhou Jing, Yang Mingkun, Wang Lei, et al. Overall Architecture Design of Manned/Unmanned Cooperation Special Combat System Based on DoDAF[J]. Ordnance Industry Automation, 2021, 40(1): 3-7.
7	孙鹏, 孙金标, 陈治湘, 等. 基于DoDAF的空中智能化作战概念体系设计[J]. 指挥控制与仿真, 2021, 43(5): 22-28.
	Sun Peng, Sun Jinbiao, Chen Zhixiang, et al. Design of Conceptual System for Air Intelligent Operations Based on DoDAF[J]. Command Control & Simulation, 2021, 43(5): 22-28.
8	杜国红, 陆树林, 郑启. 基于MBSE的作战概念建模框架研究[J]. 指挥控制与仿真, 2020, 42(3): 14-20.
	Du Guohong, Lu Shulin, Zheng Qi. Research on Operation Concept Modeling Framework Based on MBSE[J]. Command Control & Simulation, 2020, 42(3): 14-20.
9	Fahey K M, Miller M J. U.S. Department of Defense. Unmanned Systems Integrated Roadmap FY2017-2042[R]. [S.l.]: U.S. Department of Defense, 2017.
10	赵先刚. 无人作战研究[M]. 北京: 国防大学出版社, 2021.
11	郭齐胜, 樊延平, 穆歌, 等. 陆军武器装备需求论证理论与方法[M]. 北京: 电子工业出版社, 2017.
12	麻广林, 谢希权, 高明洁. 新型装备作战概念设计框架[J]. 军事运筹与系统工程, 2012, 26(1): 5-13.
13	王鹏. 陆军无人作战体系构成、运行模式及发展思路[J]. 军事学术, 2021(5): 12-15.
	Wang Peng. Structure, Operation Mode and Development Idea of Army Unmanned Combat System[J]. Military Art Journal, 2021(5): 12-15.
14	王新尧, 曹云峰, 孙厚俊, 等. 基于DoDAF的有人/无人机协同作战体系结构建模[J]. 系统工程与电子技术, 2020, 42(10): 2265-2274.
	Wang Xinyao, Cao Yunfeng, Sun Houjun, et al. Modeling for Cooperative Combat System Architecture of Manned/Unmanned Aerial Vehicle Based on DoDAF[J]. Systems Engineering and Electronics, 2020, 42(10): 2265-2274.
15	陈岩, 李志淮, 谭贤四, 等. 基于xUML的DoDAF可执行体系结构开发与验证[J]. 系统仿真学报, 2014, 26(1): 152-158.
	Chen Yan, Li Zhihuai, Tan Xiansi, et al. Design and Validation for DoDAF Executable Architecture Based on xUML[J]. Journal of System Simulation, 2014, 26(1): 152-158.
16	胡建鹏, 黄林鹏. 基于P-DEVS的可执行体系结构建模与仿真方法[J]. 系统仿真学报, 2016, 28(2): 283-291.
	Hu Jianpeng, Huang Linpeng. Modeling and Simulation of Executable Architecture Based on P-DEVS[J]. Journal of System Simulation, 2016, 28(2): 283-291.

视角类型	视图模型	概念要素	内容说明
全景视角	AV-1概述和摘要信息	概念概述	目标、任务、计划、条件等信息
	AV-1概述和摘要信息	军事威胁	系统应对的军事威胁
	AV-2综合词典	综合词典	作战概念中涉及的术语定义
能力视角	CV-1能力构想	能力需求	能力需求/缺口列项、类型、衡量指标和时间维度
	CV-2能力分类	能力特征	系统能力列项
	CV-6能力-活动映射	能力特征	能力项与作战活动的追溯关系
作战视角	OV-1高级作战概念图	作战效果	系统预期实现的作战效果
	OV-1高级作战概念图	制胜机理	系统在对抗中形成优势并导致胜利的原理
	OV-2作战资源流描述	资源交互	系统作战的资源流交互情况
	OV-3作战资源流矩阵	资源交互	资源需求线中的资源内容及相关属性
	OV-4组织关系图	系统组成	系统组件的种类、数量和比例关系以及编配信息
	OV-5a作战活动分解树	作战流程	系统主要作战活动分解
	OV-5b作战活动模型		系统主要作战活动的时序关系
	OV-6a作战规则模型		系统作战中的业务规则
	OV-6b状态转移模型	作战节点	系统作战相关节点的状态变化
	OV-6c事件跟踪描述	作战节点	系统作战相关节点的事件响应时序
数据与信息视角	DIV-1概念数据模型	信息结构	系统作战中的信息结构及其管理规则
标准视角	StdV-1标准概览	引用资源	引用的条令、指南、标准等数据资源及获取方式
标准视角	StdV-2标准预测	关键技术	系统开发所需的关键技术

资源流名称	资源流类型	来源节点	指向节点	带宽需求/Mbps
DataFlow01	数据流	指控	MGV	≥200
DataFlow02	数据流	MGV	AUGV	≥200
DataFlow03	数据流	AUGV	MGV	≥100
DataFlow04	数据流	MGV	指控	≥100
DataFlow05	数据流	AUGV	指控	≥50
CtrlFlow01	控制流	指控	MGV	≥1
CtrlFlow02	控制流	MGV	AUGV	≥2

目标	感知速度	传输速度	处理速度	决策速度	毁伤概率/%	毁伤火力
1	3	2	3	1	70	3
2	5	3	3	1	50	4
3	4	4	4	1	60	5
4	5	5	4	1	40	6

目标类型	出现时间
1	1
1	2
3	5
4	5
1	7
2	8
2	8
1	8
…	…

[1]	Liu Dayong, Dong Zhiming, Guo Qisheng, Zhang Wenjun, Gao Jiancheng. Dynamic Testing Architecture of Intelligent Unmanned Systems Based on Parallel Battlefields [J]. Journal of System Simulation, 2025, 37(8): 1933-1950.
[2]	Liu Zilong, Zhang Lei. Detection of Small Apple Targets Based on Improved YOLOv5 in Natural Environments [J]. Journal of System Simulation, 2025, 37(8): 2124-2138.
[3]	Wang Zili, Gao Yuntian, Yang Dezhen, Liu Yeyang, Ren Yi. Reliability Simulation Testing and Verification Technologies for Intelligent Systems: Frontiers, Progress, and Challenges [J]. Journal of System Simulation, 2025, 37(7): 1583-1606.
[4]	Dong Zhiming, Hu Zhongqi, Liu Zhaoyang, Zhou Heyang. A Review of Intelligent Generation of Combat Simulation Scenarios [J]. Journal of System Simulation, 2025, 37(7): 1665-1683.
[5]	Wang Bingheng, Liu Tingrui, Yang Fan, Zhang Huan, Li Wei, Ma Ping, Yang Ming. Research on Requirements and Methods for Intelligent Assessment of Simulation Credibility [J]. Journal of System Simulation, 2025, 37(7): 1710-1722.
[6]	Yang Xiujian, Huang Jingjing, Wang Xi. Modeling and Simulation of Hybrid Traffic Flow Considering the Inherent Dynamics of CACC Vehicular Platoons [J]. Journal of System Simulation, 2025, 37(6): 1388-1399.
[7]	Zhao Xuemeng, Ren Tianzhu, Fang Zhemei. Multi-model Based Iterative Method for System-of-systems Architecture Design [J]. Journal of System Simulation, 2025, 37(6): 1512-1521.
[8]	Yao Changhua, Bi Shanning, Ma Rufei, Yu Xiaohan, Li Jiaqiang, Chen Jinli. Method for Dynamic Coalition Formation of Wargame Agent for Force Cooperation [J]. Journal of System Simulation, 2025, 37(5): 1188-1196.
[9]	Dou Xiaoqiang, Liu Yan, Zhao Zhilong, Fu Chao, Zhang Fulin, Zou Shanshan. Research on Modeling Methods for Industrial Core Capability Architecture Based on the DoDAF Framework [J]. Journal of System Simulation, 2025, 37(5): 1290-1304.
[10]	Gu Qiming, Chen Jiazhi, Cao Guoyan, Zhou Chenchu, Yu Dengxiu, Hu Haifeng. Research on a Credibility Information Management Method of Simulation Modeling [J]. Journal of System Simulation, 2025, 37(5): 1314-1328.
[11]	Xu Ming, Li Jinye, Zuo Dongyu, Zhang Jing. Signal Timing Optimization via Reinforcement Learning with Traffic Flow Prediction [J]. Journal of System Simulation, 2025, 37(4): 1051-1062.
[12]	Zhou Yanzhong, Luo Junren, Gu Xueqiang, Zhang Wanpeng. Survey on Intelligent Planning Methods from Large Language Models Perspective [J]. Journal of System Simulation, 2025, 37(4): 823-844.
[13]	Zhang Huimai, Hu Xiaoya, Zhou Chunjie. Digital Twin Framework for the Generation and Optimization of Security Policies for TSN Industrial Control Systems [J]. Journal of System Simulation, 2025, 37(4): 861-874.
[14]	Zhang Bin, Lei Yonglin, Li Qun, Gao Yuan, Chen Yong, Zhu Jiajun, Bao Chenlong. Reinforcement Learning Modeling of Missile Penetration Decision Based on Combat Simulation [J]. Journal of System Simulation, 2025, 37(3): 763-774.
[15]	Su Jiongming, Luo Junren, Chen Shaofei. An Empirical Analysis of New Perspectives for Strategy Solving in Intelligent Game-theoretic Decision-making [J]. Journal of System Simulation, 2025, 37(2): 345-361.