Modeling and game strategy analysis of suppressing IADS for multiple fighters' cooperation

doi:10.21629/JSEE.2018.02.10

Journal of Systems Engineering and Electronics ›› 2018, Vol. 29 ›› Issue (2): 296-304.doi: 10.21629/JSEE.2018.02.10

• Systems Engineering • Previous Articles Next Articles

Modeling and game strategy analysis of suppressing IADS for multiple fighters' cooperation

Qiuni LI*(), Rennong YANG(), Haoliang LI(), Huan ZHANG(), Chao FENG()

Aeronautics and Astronautics Engineering College, Air Force Engineering University, Xi'an 710038, China

Received:2016-10-24 Online:2018-04-26 Published:2018-04-27
Contact: Qiuni LI E-mail:lqnjk1@126.com;yangrn6907@foxmail.com;lihaoliang10524@163.com;akzhanghuan@126.com;fengchaoacmi@outlook.com
About author:LI Qiuni was born in 1985. She received her M.S. degree in computer technology and application engineering from Aeronautics and Astronautics Engineering College, Air Force Engineering University, Xi'an, China, in 2013. She is currently pursuing her Ph.D. degree at Air Force Engineering University. Her research interests include game theory, multi-agent systems, multi-objective optimization, particularly modeling, simulation and its application. E-mail: lqnjk1@126.com|YANG Rennong was born in 1969. He received his M.S. degree in systems engineering from Aeronautics and Astronautics Engineering College, Air Force Engineering University, Xi'an, China. He is currently a professor in Aeronautics and Astronautics Engineering College, Air Force Engineering University. His main research interests include game theory, complex networks theory and optimization theory and applications. E-mail: yangrn6907@foxmail.com|LI Haoliang was born in 1989. He is a Ph.D. student at Aeronautics and Astronautics Engineering College, Air Force Engineering University. He received his M.S. degree from Air Force Engineering University in 2013. His research interests include distributed control theory, multi-agent systems, swarms and consensus theory. E-mail: lihaoliang10524@163.com|ZHANG Huan was born in 1989. He received his M.S degree in information and communication engineering from Air Force Engineering University, Xi'an, China, in 2014. He is currently pursuing his Ph.D. degree in armament science and technology in Aeronautics and Astronautics Engineering College, Air Force Engineering University. His research interests include swarm intelligence, multi-objective optimization and electronic warfare mission planning. E-mail: akzhanghuan@126.com|FENG Chao was born in 1991. He received his M.S. degree in Aeronautics and Astronautics Engineering College from Air Force Engineering University, Xi'an, China, in 2016. His research interests include multi-objective optimization and collaborative planning, particularly modeling, and simulation. E-mail: fengchaoacmi@outlook.com
Supported by:
the National Natural Science Foundation of China(61603411);This work was supported by the National Natural Science Foundation of China (61603411)

Abstract

Abstract:

This paper addresses the problem of suppression of the integrated air defense system (IADS) by multiple fighters' cooperation. Considering the dynamic changing of the number of the nodes in the operational process, a profit model for the influence of the mission's cost for the whole system is developed for both offense and defensive sides. The scenario analysis is given for the process of suppressing the IADS by multiple fighters. Based on this scenario analysis, the modeling method and the specific expression for the payoff function are proposed in four cases for each node. Moreover, a distributed virtual learning algorithm is designed for the n-person and n-strategy game, and the mixed strategy Nash equilibrium (MSNE) of this game can be solved from the n×m×3-dimensional profit space. Finally, the simulation examples are provided to demonstrate the effectiveness of the proposed model and the game algorithm.

Key words: cooperative suppression, non-cooperative game, Nash equilibrium, virtual learning

Qiuni LI, Rennong YANG, Haoliang LI, Huan ZHANG, Chao FENG. Modeling and game strategy analysis of suppressing IADS for multiple fighters' cooperation[J]. Journal of Systems Engineering and Electronics, 2018, 29(2): 296-304.

Figures/Tables 8

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References 20

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Parameter	Detecting domain A/km	Offensive domain B/km	Damage capacity C	ValueP_c/(104CNY)	SpeedV /(km/h)	Weight of connection w_mj	Detecting probabilityP_d	Attacking probabilityP_k
Range	(0, 100)	(5, 30)	(10, 100)	(10, 1 000)	(100, 1 000)	(0, 1)	(0.5, 0.99)	(0.5, 0.99)

Number of nodes	The nodes' average expected payoffs(adjacent algorithm, virtual learning)	The nodes' total expected payoffs(adjacent algorithm, virtual learning)
n=3, m=10	(0.023 7, 0.028 9)	(17.99, 21.71)
n=5, m=15	(0.017 3, 0.023 5)	(21.34, 27.13)

[1]	Guopeng Zhang, Peng Liu, and Enjie Ding. Energy efficient resource allocation in non-cooperative multi-cell OFDMA systems [J]. Journal of Systems Engineering and Electronics, 2011, 22(1): 175-182.
[2]	Xiaohui Yu and Qiang Zhang. Fuzzy Nash equilibrium of fuzzy n-person non-cooperative game [J]. Journal of Systems Engineering and Electronics, 2010, 21(1): 47-56.

Modeling and game strategy analysis of suppressing IADS for multiple fighters' cooperation

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