Journal of Systems Engineering and Electronics ›› 2024, Vol. 35 ›› Issue (5): 1190-1210.doi: 10.23919/JSEE.2024.000114
收稿日期:2022-10-12
									
				
									
				
									
				
											出版日期:2024-10-18
									
				
											发布日期:2024-11-06
									
			
        
               		Wei LI(
), Yue WANG(
), Lijuan JIA(
), Senran PENG(
), Ruixi HE(
)
			  
			
			
			
                
        
    
Received:2022-10-12
									
				
									
				
									
				
											Online:2024-10-18
									
				
											Published:2024-11-06
									
			Contact:
					Lijuan JIA   
											E-mail:18522191168@163.com;wangyue@bit.edu.cn;jlj@bit.edu.cn;pengsenran1997@163.com;cheneyhe2016@163.com
												About author:Supported by:. [J]. Journal of Systems Engineering and Electronics, 2024, 35(5): 1190-1210.
Wei LI, Yue WANG, Lijuan JIA, Senran PENG, Ruixi HE. Battlefield target intelligence system architecture modeling and system optimization[J]. Journal of Systems Engineering and Electronics, 2024, 35(5): 1190-1210.
"
| Organizational node | Organizational element | 
| Reconnaissance sensor | Reconnaissance satellite, reconnaissance sensor of reconnaissance aircraft, reconnaissance drone,  radar detection end, reconnaissance sensor of reconnaissance vehicle, reconnaissance sensor of the reconnaissance ship  | 
| Sensor console | Satellite earth station, reconnaissance console of reconnaissance aircraft, UAV ground station, radar console, reconnaissance console of reconnaissance vehicle, reconnaissance console of the reconnaissance ship  | 
| Intelligence center | Intelligence center | 
| Client | Command post, weapon platform, combat unit | 
"
| Organizational node | Running resource | 
| Reconnaissance sensor | Photoelectric sensors, radar, positioning and ranging equipment, electronic reconnaissance sensors,  sonar sensors, information transceiver equipment  | 
| Sensor console | Reconnaissance data preprocessing module,  reconnaissance data positioning and identification processing module, information transceiver equipment, sensor control module  | 
| Intelligence center | Information transceiver equipment, intelligence fusion module, intelligence storage module, intelligence distribution module, command and control module  | 
| Client | Information transceiver equipment, information  display equipment, fire control system, human-computer interaction equipment  | 
"
| Serial number | Information element | Source node | Source node activity | Destination node | Destination node activity | 
| 1 | Demand information | Clients | Propose intelligence demands | Intelligence center | Develop reconnaissance plans | 
| 2 | Reconnaissance order | Intelligence center | Give reconnaissance orders | Sensor consoles | Control reconnaissance sensor | 
| 3 | Control commands | Sensor consoles | Control reconnaissance sensor | Reconnaissance sensors | Conduct reconnaissance | 
| 4 | Target reconnaissance data | Reconnaissance sensors | Sending data | Sensor consoles | Receive data | 
| 5 | Target identification and  positioning information  | Sensor consoles | Send processed intelligence information | Intelligence center | Receive intelligence information | 
| 6 | Intelligence products | Intelligence center | Distribute intelligence products | Clients | Receive and display  intelligence products  | 
"
| Organizational node | Running action | 
| Reconnaissance sensor | Conduct reconnaissance Send data to the sensor console  | 
| Sensor console | Control sensors start reconnaissance Preprocess reconnaissance data Determine whether the data meets the processing requirements Conduct identification and positioning processing Send intelligence information to intelligence center  | 
| Intelligence center | Develop reconnaissance plans Assign reconnaissance tasks, give reconnaissance orders Fuse and process target intellifence Determine whether the target intelligence meets the mission requirements Storage and distribute targeted intelligence products  | 
| Client | Propose intelligence demands Receive and display intelligent content  | 
"
| Organization node that generates information  | Information element | 
| Reconnaissance sensor  | Target reconnaissance data: optical  image data, radar detection data, electromagnetic radiation source signal data, distance measurement data, sonar detection data  | 
| Sensor console | Control commands Target identification and positioning information  | 
| Intelligence center | Reconnaissance order Intelligence products  | 
| Client | Demand information | 
"
| Running action | System function | 
| Reconnaissance | Optical photo reconnaissance function Radar detection reconnaissance function Electronic reconnaissance function Distance measuring function Sonar detection reconnaissance function  | 
| The sensor console controls the sensor to start reconnaissance | Control sensor function | 
| Preprocessing of reconnaissance data | Reconnaissance data preprocessing function | 
| Identification and location processing of reconnaissance data | Reconnaissance data identification processing function Reconnaissance data location processing function  | 
| Develop reconnaissance plans | Develop reconnaissance plan function | 
| Perform target intelligence fusion processing | Perform target intelligence fusion processing function | 
| Store and distribute target intelligence | Target intelligence storage function Target intelligence distribution function  | 
| Receive and display intelligent content | Demonstrate target intelligence product function | 
"
| Optimization direction | Predictive technology 1 | Predictive technology 2 | Predictive technology 3 | 
| Intelligence processing function | Data annotation accumulation, building target datasets [ | Automatic target recognition and positioning processing technology [ | − | 
| Intelligence fusion function | Intelligence information automatic fusion technology [  | − | − | 
| Intelligence distribution function | Intelligent distribution technology [ | − | − | 
| Information interaction function | New generation data link technology [ | − | − | 
| Security and confidentiality function | Blockchain technology [ | General computing platform localization  technology [  | − | 
| Command and control function | Intelligent intelligence staff technology [  | Unmanned platform collaborative command and control technology [ | − | 
| Information system computing architecture | Cloud computing technology [ | Edge computing technology [ | Fog computing technology [ | 
| 1 | FU X H, SHEN J, LUO B G Design and implementation of reconnaissance monitoring system in battlefield. Applied Mechanics and Materials, 2014, 3252 (568/570): 528- 532. | 
| 2 | LI C X, WANG C, XU Y, et al Functional model construction of unified battlefield situation map under joint operation. Modern Radar, 2022, 44 (2): 35- 40. | 
| 3 | WANG Y. System theory and artificial system design. Beijing: Beijing Institute of Technology Press, 2019. (in Chinese) | 
| 4 | DoD Architecture Framework Working Group. DoD architecture framework Version 2.0 Volume 1: introduction, overview, and concepts. Washington D.C.: US Department of Defense, 2009. | 
| 5 | DoD Architecture Framework Working Group. DoD architecture framework Version 2.0 Volume 2: architectural data and modes. Washington D.C.: US Department of Defense, 2009. | 
| 6 |  
											 XING D H, CHEN W Y Systematic method of applying structural characteristics of natural organisms to mechanical structures. Transactions of Tianjin University, 2011, 17 (4): 293- 297. 
											 												 doi: 10.1007/s12209-011-1643-z  | 
										
| 7 | GODLEVSKYI M D, ORLOVSKYI D L, KOPP A M Structural analysis and optimization of IDEF0 functional business process models. Radio Electronics, Computer Science, Control, 2018, 46 (3): 48- 56. | 
| 8 | LIU S, LIU Y F, YIN L. Thoughts on the construction of intelligent information system in the field of reconnaissance and intelligence. Journal of Command and Control, 2024, 10(2): 250−254. (in Chinese) | 
| 9 | YUAN C, DU B, YU P H, et al Research on situational awareness technology of battlefield environment based on multi-agent cooperation. Proc. of the 6th International Conference on Mechatronics and Intelligent Robotics, 2022, 123010T. | 
| 10 | CAO J, GAO L L Interoperable, understandable, compliant the novel capability goal and evaluation model for military information system. Journal of Command and Control, 2015, 1 (1): 41- 45. | 
| 11 | China Electronics Technology Group Corporation Development Strategy Research Center. World military electronics annual development report. Beijing: Electronic Industry Press, 2018. (in Chinese) | 
| 12 | HUANG Z L, SHEN Y, HU B, et al Review of the development of military intelligence recommendation technology. Science Technology and Engineering, 2020, 20 (15): 5900- 5909. | 
| 13 | SHI F, CAI S J, LI W Research for military information system based on domestic key software and hardware. Informatization Research, 2016, 42 (4): 14- 16, 27. | 
| 14 | HUANG Q N, ZHU W G, LI Y G Summary of research on construction SAR image ship target detection dataset. Telecommunication Engineering, 2021, 61 (11): 1451- 1458. | 
| 15 | DINESH V, GREG C, TIEN P, et al Generation and management of training data for AI-based algorithms targeted at coalition operations. Defense+Security, 2018, 10635, 209- 216. | 
| 16 | JAMES S H Analytical use of data from army training exercises: a case study of tactical reconnaissance. Journal of the American Statistical Association, 2012, 89 (426): 444- 451. | 
| 17 |  
											 YANG H, ZHANG Y S, YIN C B, et al Ultra-lightweight CNN design based on neural architecture search and knowledge distillation: a novel method to build the automatic recognition model of space target ISAR images. Defence Technology, 2022, 18 (6): 1073- 1095. 
											 												 doi: 10.1016/j.dt.2021.04.014  | 
										
| 18 |  
											 HU X D, WANG X Q, YANG X, et al An infrared target intrusion detection method based on feature fusion and enhancement. Defence Technology, 2020, 16 (3): 737- 746. 
											 												 doi: 10.1016/j.dt.2019.10.005  | 
										
| 19 |  
											 HAN Z S, WANG C P, FU Q Arbitrary-oriented target detection in large scene sar images. Defence Technology, 2020, 16 (4): 933- 946. 
											 												 doi: 10.1016/j.dt.2019.11.014  | 
										
| 20 |  
											 ARIVAZHAGAN S, PRIYADHARSHINI R A, SANGEETHA L Automatic target recognition in SAR images using quaternion wavelet transform and principal component analysis. International Journal of Computational Vision and Robotics, 2017, 7 (3): 314- 334. 
											 												 doi: 10.1504/IJCVR.2017.083449  | 
										
| 21 |  
											 GONG Y M, MA Z Y, WANG M J, et al A new multi-sensor fusion target recognition method based on complementarity analysis and neutrosophic set. Symmetry, 2020, 12 (9): 1435- 1435. 
											 												 doi: 10.3390/sym12091435  | 
										
| 22 | SUMARI A, AHMAD A S Design and implementation of multi agent-based information fusion system for supporting decision making (a case study on military operation). Journal of ICT Research and Applications, 2013, 2 (1): 42- 63. | 
| 23 |  
											 SYCARA K, GLINTON R, YU B, et al An integrated approach to high-level information fusion. Information Fusion, 2009, 10 (1): 25- 50. 
											 												 doi: 10.1016/j.inffus.2007.04.001  | 
										
| 24 | NIU B, HUANG Z L, WU J J, et al. Modeling of intelligence recommendation based on UML. Proc. of the International Conference on Advanced Manufacturing Technology and Manufacturing Systems, 2022: 123092X. | 
| 25 | LI L Q. Cross-border E-commerce intelligent information recommendation system based on deep learning. Computational Intelligence and Neuroscience, 2022, 2022: 6602471. | 
| 26 | YANG A S, LI S M, WU Y J, et al. Turbo equalization technique for data link communication systems. Proc. of the 5th International Conference on Wireless Communications and Applications, 2021: 101−110. | 
| 27 | YAO G Method for improving trajectory tracking accuracy in sea area of airborne data link. Arabian Journal of Geosciences, 2021, 14, 512. | 
| 28 |  
											 CHEN Z, ZHAI R, LI D C, et al Performance evaluation of a tactical data-link system based on MSK and 16QAM. IEEE Access, 2021, 9, 84316- 84326. 
											 												 doi: 10.1109/ACCESS.2021.3086048  | 
										
| 29 | MA J K, WANG X Y, CHEN K W, et al. Design and study UAV data link terminal with one station controls several vehicles dynamic networking. Journal of Physics: Conference Series, 2020, 1486(5): 052015. | 
| 30 | LI J, DANG X Y, LI S DQN-based decentralized multi-agent JSAP resource allocation for UAV swarm communication. Journal of Systems Engineering and Electronics, 2023, 34 (2): 289- 298. | 
| 31 | CHEN J, WU J Y, QIAN Z H, et al. Industrial chain data sharing and circulation of blockchain and big data technology. Wireless Communications and Mobile Computing, 2022, 2022: 7719036. | 
| 32 | RAJASOUNDARAN S, KUMAR S V N S, SELVI M, et al. Machine learning based volatile block chain construction for secure routing in decentralized military sensor networks. Molecular Human Reproduction, 2021, 27(7): 4513−4534. | 
| 33 | IRSHAD A, CHAUDHRY S A, GHANI A, et al A secure blockchain-oriented data delivery and collection scheme for 5G-enabled IoD environment. Computer networks, 2021, 195, 108219. | 
| 34 |  
											 FENG W, LI Y F, YANG X T, et al Blockchain-based data transmission control for tactical data link. Digital Communications and Networks, 2021, 7 (3): 285- 294. 
											 												 doi: 10.1016/j.dcan.2020.05.007  | 
										
| 35 | LING Y Z, WANG F G, LYU M M. Research on the design of nationalized of intelligent 1553B communication module. Pro. of the 2nd International Conference on Digital Signal and Computer Communications, 2022: 123060B. | 
| 36 |  
											 CALAMIA J China’s homegrown supercomputers. IEEE Spectrum, 2012, 49 (1): 60- 62. 
											 												 doi: 10.1109/MSPEC.2012.6117842  | 
										
| 37 | HEER P D, REUS N D, TEALDI L, et al. Intelligence augmentation for urban warfare operation planning using deep reinforcement learning. Proc. of the Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications, 2019. DOI: 10.1117/12.20051. | 
| 38 | SUSNEA E Decision support systems in military actions: necessity, possibilities and constraints. Journal of Defense Resources Management, 2012, 3 (2): 131- 140. | 
| 39 | YOO D, NO S, RA M A practical military ontology construction for the intelligent army tactical command information system. International Journal of Computers Communications & Control, 2014, 9 (1): 93- 100. | 
| 40 | HANRATTY T P, NEWCOMB E A, HAMMELL R J, et al A fuzzy-based approach to support decision making in complex military environments. International Journal of Intelligent Information Technologies, 2016, 12 (1): 1- 30. | 
| 41 | ZHAO X Y, YANG M, PENG C, et al. Research on intelligent operational assisted decision-making of naval battlefield based on deep reinforcement learning. Proc. of the 3rd International Conference on Advanced Information Science and System, 2021: 59−65. | 
| 42 | FU M R, XU Y W, YU Z Q, et al. Decentralized adaptive fault-tolerant cooperative control for multiple UAVs with input saturation and state constraints. International Journal of Aerospace Engineering, 2022, 2022: 8385913. | 
| 43 |  
											 ZHANG J M, YUE X K, ZHANG H F, et al Optimal unmanned ground vehicle—unmanned aerial vehicle formation-maintenance control for air-ground cooperation. Applied Sciences, 2022, 12 (7): 3598. 
											 												 doi: 10.3390/app12073598  | 
										
| 44 | ANTONIO V T J, ADRIEN G, MANUEL A M, et al Event-triggered leader-following formation control for multi-agent systems under communication faults: application to a fleet of unmanned aerial vehicles. Journal of Systems Engineering and Electronics, 2021, 32 (5): 1014- 1022. | 
| 45 | FANG J Y, HAN Y, ZHOU Z L, et al. The collaborative combat of heterogeneous multi-UAVs based on MARL. Journal of Physics: Conference Series, 2021, 1995: 012023. | 
| 46 | XU D, CHEN G The research on intelligent cooperative combat of UAV cluster with multi-agent reinforcement learning. Aerospace Systems, 2021, 5, 107- 121. | 
| 47 |  
											 FAN J R, LI D G, LI R P, et al Analysis on MAV/UAV cooperative combat based on complex network. Defence Technology, 2020, 16 (1): 150- 157. 
											 												 doi: 10.1016/j.dt.2019.09.002  | 
										
| 48 |  
											 WANG Y C, ZHANG N, LI H S, et al Research on digital twin framework of military large-scale UAV based on cloud computing. Journal of Physics: Conference Series, 2021, 1738 (1): 012052. 
											 												 doi: 10.1088/1742-6596/1738/1/012052  | 
										
| 49 |  
											 KOO J, KIM Y G, LEE S H Design of security architecture for the cloud-based korea military command and control system. The Journal of Korean Institute of Communications and Information Sciences, 2020, 45 (2): 400- 408. 
											 												 doi: 10.7840/kics.2020.45.2.400  | 
										
| 50 |  
											 MAROZZO F, BELCASTRO L Cloud computing for big data analysis. Applied Sciences, 2022, 12 (20): 10567. 
											 												 doi: 10.3390/app122010567  | 
										
| 51 | JAWED S M, SAJID M A comprehensive survey on cloud computing: architecture, tools, technologies, and open issues. International Journal of Cloud Applications and Computing, 2022, 12 (1): 1- 33. | 
| 52 | HASSAN M M, HASSAN M R, DE ALBUQUERQUE V H C, et al. Soft computing for intelligent edge computing. Applied Soft Computing, 2022, 128: 109628. | 
| 53 |  
											 CORCHADO J M, OSSOWSKI S, RODRIGUEZGONZALEZ S, et al Advances in explainable artificial intelligence and edge computing applications. Electronics, 2022, 11 (19): 3111. 
											 												 doi: 10.3390/electronics11193111  | 
										
| 54 | JEON G, ALBERTINI M, BELLANDI V, et al Intelligent mobile edge computing for IoT big data. Complex & Intelligent Systems, 2022, 8 (5): 3595- 3601. | 
| 55 |  
											 SONG Z Y, QIN X T, HAO Y Y, et al A comprehensive survey on aerial mobile edge computing: challenges, state-of-the-art, and future directions. Computer Communications, 2022, 191, 233- 256. 
											 												 doi: 10.1016/j.comcom.2022.05.004  | 
										
| 56 |  
											 BUKHARI A, HUSSAIN F K, HUSSAIN O K Fog node discovery and selection: a systematic literature review. Future Generation Computer Systems, 2022, 135, 114- 128. 
											 												 doi: 10.1016/j.future.2022.04.034  | 
										
| 57 |  
											 SABIREEN H, NEELANARAYANAN V A review on fog computing: architecture, fog with IoT, algorithms and research challenges. ICT Express, 2021, 7 (2): 162- 176. 
											 												 doi: 10.1016/j.icte.2021.05.004  | 
										
| 58 | JUAN J L E, REBECA P D R, FELIPE G C. In-depth analysis and open challenges of mist computing. Journal of Cloud Computing, 2022, 11: 81. | 
| 59 | WEI J C, ZHANG J, YANG W Y, et al. Modeling for integrated disposal system architecture of low-slow-small aerocraft based on DoDAF. Systems Engineering and Electronics, 2023, 46(1): 162−172. (in Chinese) | 
| No related articles found! | 
| 阅读次数 | ||||||
| 
												        	全文 | 
											        	
												        	 | 
													|||||
| 
												        	摘要 | 
												        
															 | 
													|||||