A function-based behavioral modeling method for air combat simulation

doi:10.23919/JSEE.2024.000068

Journal of Systems Engineering and Electronics ›› 2024, Vol. 35 ›› Issue (4): 945-954.doi: 10.23919/JSEE.2024.000068

• SYSTEMS ENGINEERING • Previous Articles Next Articles

A function-based behavioral modeling method for air combat simulation

Tao WANG¹(), Zhi ZHU¹^,*(), Xin ZHOU¹(), Tian JING¹(), Wei CHEN²()

¹ College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
² Institute of Communication and Navigation, Air Force Research Academy, Beijing 100085, China

Received:2023-12-11 Online:2024-08-18 Published:2024-08-06
Contact: Zhi ZHU E-mail:wangtao1976@nudt.edu.cn;zhuzhi@nudt.edu.cn;zhouxin09@nudt.edu.cn;jingtian16@nudt.edu.cn;weichen@nudt.edu.cn
About author:
WANG Tao was born in 1976. He received his Ph.D. degree from National University of Defense Technology. He is a professor at the National University of Defense Technology. He is the director of the Department of Strategy Management Engineering. His research interests include strategy planning, multi-agent simulation, and data mining. E-mail: wangtao1976@nudt.edu.cn

ZHU Zhi was born in 1989. He received his Ph.D. degree from National University of Defense Technology. He is an assistant professor at National University of Defense Technology, China. He was a visiting Ph.D. student at the Arizona State University from 2016 to 2017. His research interests are model-driven development, systems engineering and machine learning. E-mail: zhuzhi@nudt.edu.cn

ZHOU Xin was born in 1990. He received his Ph.D. degree from National University of Defense Technology. He is an assistant professor at National University of Defense Technology. His research interests are systems engineering, simulation modeling and reinforcement learning. E-mail: zhouxin09@nudt.edu.cn

JING Tian was born in 1993. He received his Ph.D. degree from National University of Defense Technology. He is an assistant professor at National University of Defense Technology. He is now pursuing his Ph.D. degree at National University of Defense Technology. His research interests are systems engineering, unmanned aerial vehicle swarm and simulation engineering. E-mail: jingtian16@nudt.edu.cn

CHEN Wei was born in 1993. He received his Ph.D. degree from Leiden University, Netherlands. He is a senior engineer at the Air Force Research Academy, China. His research interests are deep learning, image processing, and air combat. E-mail: weichen@nudt.edu.cn
Supported by:
This work was supported by the National Natural Science Foundation of China (62003359).

Abstract

Abstract:

Today’s air combat has reached a high level of uncertainty where continuous or discrete variables with crisp values cannot be properly represented using fuzzy sets. With a set of membership functions, fuzzy logic is well-suited to tackle such complex states and actions. However, it is not necessary to fuzzify the variables that have definite discrete semantics. Hence, the aim of this study is to improve the level of model abstraction by proposing multiple levels of cascaded hierarchical structures from the perspective of function, namely, the functional decision tree. This method is developed to represent behavioral modeling of air combat systems, and its metamodel, execution mechanism, and code generation can provide a sound basis for function-based behavioral modeling. As a proof of concept, an air combat simulation is developed to validate this method and the results show that the fighter Alpha built using the proposed framework provides better performance than that using default scripts.

Key words: air combat, behavioral modeling, intelligent agent

Tao WANG, Zhi ZHU, Xin ZHOU, Tian JING, Wei CHEN. A function-based behavioral modeling method for air combat simulation[J]. Journal of Systems Engineering and Electronics, 2024, 35(4): 945-954.

Figures/Tables 9

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Number	Alpha			Fighter
Number	Altitude/m	Velocity/(m/s)	Mission completed	Altitude/m	Velocity/(m/s)	Mission completed
1	12000	250	0	12000	250	1
2	12000	250	1	12000	300	0
3	12000	250	1	12000	350	0
4	12000	250	0	6000	250	0
5	12000	250	1	6000	300	0
6	12000	250	1	6000	350	0
7	12000	250	1	9000	250	0
8	12000	250	1	9000	300	0
9	12000	250	1	9000	350	0
10	12000	300	1	12000	250	0

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A function-based behavioral modeling method for air combat simulation

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