Investigation of MAS structure and intelligent+ information processing mechanism of hypersonic target detection and recognition system

doi:10.23919/JSEE.2020.000083

Journal of Systems Engineering and Electronics ›› 2020, Vol. 31 ›› Issue (6): 1105-1115.doi: 10.23919/JSEE.2020.000083

• ELECTRONICS TECHNOLOGY • Previous Articles Next Articles

Investigation of MAS structure and intelligent⁺ information processing mechanism of hypersonic target detection and recognition system

Xia WU(), Yan LI*(), Yongjian SUN(), Alei CHEN(), Jianwen CHEN(), Jianchao MA(), Hao CHEN()

¹ Radar Sergeant School, Air Force Early-Warning Academy, Wuhan 430019, China

Received:2019-11-01 Online:2020-12-18 Published:2020-12-29
Contact: Yan LI E-mail:moonshiner007@163.com;107667456@qq.com;bmdsun@126.com;26924791@qq.com;cjwll8217@vip.sina.com;549464509@qq.com;ch19930922@163.com
About author:|WU Xia was born in 1979. He received his M.E. degree in 2006, and Ph.D. degree in 2011 from Air Force Early-Warning Academy. He is a lecturer at Air Force Early-Warning Academy now. His research interests include target detection, target recognition and information fusion. E-mail: moonshiner007@163.com||LI Yan was born in 1985. She received her B.A. degree in 2008 from Wuhan University of Science and Technology, and M.E. degree in 2016 from Central China Normal University, She is a lecturer at Air Force Early-Warning Academy now. Her research interests include target recognition, english applied linguistics and military english. E-mail: 107667456@qq.com||SUN Yongjian was born in 1976. He received his M.E. degree from Air Force Early-Warning Academy in 2006 and Ph.D. degree from the Second Research Institute of the China Aerospace Science and Industry Corporation Limited in 2014. He is a lecturer at Air Force Early-Warning Academy now. His research interests include radar system, radar signal processing, radar data processing and automatic target recognition. E-mail: bmdsun@126.com||CHEN Alei was born in 1982. He received his B.S., M.S., and Ph.D. degrees from Air Force Early-Warning Academy, in 2004, 2007, and 2011, respectively. His main research interests include radar system, target detection, and over-the-horizon radar signal processing. E-mail: 26924791@qq.com||CHEN Jianwen was born in 1964. He received his Ph.D. degree in 2000 from National University of Defense Technology. Now he is a professor and doctorial student supervisor of Air Force Early-Warning Academy. His research interests include array signal processing and radar system. E-mail: cjwll8217@vip.sina.com||MA Jianchao was born in 1972. He received his B.A. degree in 1994, and M.E. degree in 2016 from Air Force Early-Warning Academy. He is a professor at Air Force Early-Warning Academy now. His research interest is intelligent information processing. E-mail: 549464509@qq.com||CHEN Hao was born in 1993. He received his B.A. degree in 2012, and M.E. degree in 2016 fom Air Force Early-Warning Academy. Now he works as an assistant at Air Force Early-Warning Academy. His research interests include array signal processing and radar signal processing. E-mail: ch19930922@163.com
Supported by:
This work was supported by the National Natural Science Foundation of China (61471391)

Abstract

Abstract:

The hypersonic target detection and recognition system is studied, on the basis of overall planning and design, a multi-agent system (MAS) structure and intelligent⁺ information processing mechanism based on target detection and recognition are proposed, and the multi-agent operation process is analyzed and designed in detail. In the specific agents construction, the information fusion technology is introduced to defining the embedded agents and their interrelations in the system structure, and the intelligent processing ability of complex and uncertain problems is emphatically analyzed from the aspects of autonomy and collaboration. The aim is to optimize the information processing strategy of the hypersonic target detection and recognition system and improve the robustness and rapidity of the system.

Key words: hypersonic target, detection recognition, intelligent information fusion, multi-agent system (MAS)

Xia WU, Yan LI, Yongjian SUN, Alei CHEN, Jianwen CHEN, Jianchao MA, Hao CHEN. Investigation of MAS structure and intelligent⁺ information processing mechanism of hypersonic target detection and recognition system[J]. Journal of Systems Engineering and Electronics, 2020, 31(6): 1105-1115.

Figures/Tables 8

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References 19

1	HUANG Z C Hypersonic weapons and its influence on future war. Tactical Missile Technology, 2018, (3): 1- 7.
2	MARK J L Hypersonic weapons come of age. Air Force Magazine, 2016, (3): 47- 51.
3	NORRIS G. U.S. Air Force plans road map to operational hypersonic. [2017−07−27]. http://aviationweek.com/defense/us-air-force-plans-road-map-operational-hypersonics.
4	SUN W, WANG Q, FU Q, et al Multi-sensors mission distribution algorithm of near space hypersonic vehicle. Fire Control & Command Control, 2017, 42 (12): 81- 87.
5	FU Q, WANG G, GUO X K, et al Requirements analysis on collaborative detection and tracking of near space high-speed targets. Systems Engineering and Electronics, 2015, 37 (4): 757- 762.
6	XIAO S, TAN X S, WANG H, et al Deployment optimization method for ground-based radar to detect near space hypersonic targets. Journal of National University of Defense Technology, 2015, 37 (2): 121- 127.
7	MICHELE A, SERGIO C, FOLKER W Sensor data fusion for activity monitoring in the PERSONA ambient assisted living project. Journal of Ambient Intelligence and Humanized Computing, 2016, 4 (1): 67- 84.
8	JIN H X, YANG T, WANG X G, et al Application of multi-sensor information fusion in UAV relative navigation method. Journal of National University of Defense Technology, 2017, 39 (7): 90- 95.
9	LI X L, WANG J, LUO X Y. Adaptive finite-time consensus of nonlinear multi-agent systems with unknown dynamics and disturbances. Proc. of the 36th Chinese Control Conference, 2017: 8621−8626.
10	MA L F, WANG Z D, HAN Q L, et al Consensus control of stochastic multi-agent systems: a survey. Science China (Information Sciences), 2017, 60 (12): 201- 215.
11	XUE L, WANG Q L, SUN C Y Game theoretical approach for the leader selection of the second-order multi-agent system. Control Theory and Applications, 2016, 33 (12): 1593- 1602.
12	HE R, LUO X M Study MAS-based command system modeling of missile defense systems operation. Command Control & Simulation, 2017, 39 (2): 5- 9.
13	ZHANG R. Research on multi-agent-based synergic decision technologies for aircraft assignment. Nanjing: Nanjing University of Aeronautics and Astronautics, 2017. (in Chinese)
14	LIN Z Z, CHEN T P, LU W L. Finite-time synchronization for nonlinear multi-agent system with directed structure by iterative learning control. Proc. of the 36th Chinese Control Conference, 2017: 8542−8547.
15	ZHANG X, WANG J H, YANG D D, et al Tracking consensus for heterogeneous multi-agent systems subject to unknown disturbances via sliding mode control. Chinese Physics B, 2017, 26 (7): 43- 52.
16	WU X, CHEN J W, LU K Investigation of system structure and information processing mechanism for cognitive skywave over-the-horizon radar. Journal of Systems Engineering and Electronics, 2016, 27 (4): 797- 806. doi: 10.21629/JSEE.2016.04.08
17	WU X, ZHOU Y, YANG L P, et al Target feature sensitivity evaluation method based on cluster analysis and geometry. Control and Decision, 2012, 27 (6): 914- 918.
18	GUAN X, LIU H Q, YI X, et al Probability transformation based on the conflict degree of feedback evidence. Systems Engineering and Electronics, 2018, 40 (7): 1436- 1442.
19	WU X, ZHOU Y Method of information fusion based on fuzzy sensor and interval multi-attribute decision-making. Journal of Astronautics, 2011, 32 (6): 1409- 1415.

Characteristic	Phase1	Phase2	Phase3
Technology 1	1	0	1
Technology 2	1	1	1
Technology 3	1	1	0
Technology 4	0	0	1

Target	Recognition method	Belief function v_i				Recognition result
Target	Recognition method	f₁	f₂	f₃	f₄	Recognition result
	Technology 1	0.421	0.325	0.154	0.100	Uncertainty
	Technology 2	0.404	0.334	0.132	0.130	Uncertainty
Target 1	Technology 3	?	?	?	?	?
	Technology 4	0.444	0.204	0.312	0.140	Uncertainty
	Fuzzy fusion agent	0.640	0.150	0.106	0.104	f₁
	DS fusion agent	0.598	0.112	0.180	0.110	f₁
	Technology 1	0.215	0.356	0.289	0.140	Uncertainty
	Technology 2	0.231	0.424	0.245	0.100	Uncertainty
Target 2	Technology 3	?	?	?	?	?
	Technology 4	0.288	0.435	0.146	0.131	Uncertainty
	Fuzzy fusion agent	0.270	0.418	0.165	0.147	Uncertainty
	DS fusion agent	0.208	0.566	0.123	0.103	f₂
	Technology 1	0.443	0.121	0.136	0.300	Uncertainty
	Technology 2	0.278	0.426	0.191	0.105	Uncertainty
Target 3	Technology 3	?	?	?	?	?
	Technology 4	0.291	0.424	0.181	0.104	Uncertainty
	Fuzzy fusion agent	0.112	0.213	0.565	0.110	f₃
	DS fusion agent t	0.156	0.201	0.559	0.084	f₃
Target 4	Technology 1	0.154	0.107	0.061	0.678	f₄
	Technology 2	0.121	0.120	0.172	0.587	f₄
	Technology 3	?	?	?	?	?
	Technology 4	0.134	0.014	0.179	0.673	f₄
	Fuzzy fusion agent	0.176	0.038	0.151	0.635	f₄
	DS fusion agent	0.160	0.101	0.102	0.637	f₄

[1]	Lin LI, Guohong WANG, Dianxing SUN, Xiangyu ZHANG. A hypersonic target coherent integration detection algorithm based on Doppler feedback [J]. Journal of Systems Engineering and Electronics, 2020, 31(1): 85-94.
[2]	Zihe Gao, Qing Guo, and Zhenyu Na. Novel optimized routing algorithm for LEO satellite IP networks [J]. Journal of Systems Engineering and Electronics, 2011, 22(6): 917-925.

Investigation of MAS structure and intelligent⁺ information processing mechanism of hypersonic target detection and recognition system

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