Battlefield target intelligence system architecture modeling and system optimization

doi:10.23919/JSEE.2024.000114

Journal of Systems Engineering and Electronics ›› 2024, Vol. 35 ›› Issue (5): 1190-1210.doi: 10.23919/JSEE.2024.000114

• SYSTEMS ENGINEERING • Previous Articles Next Articles

Battlefield target intelligence system architecture modeling and system optimization

Wei LI(), Yue WANG(), Lijuan JIA(), Senran PENG(), Ruixi HE()

School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China

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:
LI Wei was born in 1989. He received his B.S. degree in communication engineering from PLA University Science and Technology, Nanjing, China, in 2012. He has been pursuing his M.S. degree at Beijing Institute of Technology since 2020. His research interests include complex system theory, multi-living agent theory, and battlefield intelligence systems. E-mail: 18522191168@163.com

WANG Yue was born in 1932. He received his B.S. degree in radar engineering from Xidian University, Xi’an, China, in 1956. He was the president of the No. 206 Institute of China North Industries Group Corporation, and the president of Beijing Institute of Technology from 1993 to 1997. He is now the honorary president and a professor of Beijing Institute of Technology. He is an academician of both the Chinese Academy of Sciences and the Chinese Academy of Engineering. His research interests include signal processing and complex information system theory and technology. E-mail: wangyue@bit.edu.cn

JIA Lijuan was born in 1968. She received her Ph.D. degree in electrical and electronic engineering from Kyushu University, Japan, in 2002. Since 2005, she has been an associate professor at the School of Information and Electronics, Beijing Institute of Technology. Her research interests include multi-living agent system theory, distributed adaptive networks, and statistical signal processing. E-mail: jlj@bit.edu.cn

PENG Senran was born in 1997. He received his B.S. degree in information engineering from the School of Information, Zhuhai Campus, Beijing Institute of Technology, in 2019. Now he is working toward his Ph.D. degree with the School of Information and Electronics, Beijing Institute of Technology. His research interests include distributed multi-agent system theory, complex system theory, and adaptive signal processing. E-mail: pengsenran1997@163.com

HE Ruixi was born in 1998. He received his B.S. degree in electronic information engineering from the Faculty of Information Science and Engineering, Ocean University of China in 2020. In 2023, he received his M.S. degree at Beijing Institute of Technology. His research interests are computer vision and machine learning. E-mail: cheneyhe2016@163.com
Supported by:
This work was supported by the National Natural Science Foundation of China (41927801).

Abstract

Abstract:

To address the current problems of poor generality, low real-time, and imperfect information transmission of the battlefield target intelligence system, this paper studies the battlefield target intelligence system from the top-level perspective of multi-service joint warfare. First, an overall planning and analysis method of architecture modeling is proposed with the idea of a bionic analogy for battlefield target intelligence system architecture modeling, which reduces the difficulty of the planning and design process. The method introduces the Department of Defense architecture framework (DoDAF) modeling method, the multi-living agent (MLA) theory modeling method, and other combinations for planning and modeling. A set of rapid planning methods that can be applied to model the architecture of various types of complex systems is formed. Further, the liveness analysis of the battlefield target intelligence system is carried out, and the problems of the existing system are presented from several aspects. And the technical prediction of the development and construction is given, which provides directional ideas for the subsequent research and development of the battlefield target intelligence system. In the end, the proposed architecture model of the battlefield target intelligence system is simulated and verified by applying the colored Petri nets (CPN) simulation software. The analysis demonstrates the reasonable integrity of its logic.

Key words: battlefield target intelligence system, architecture modeling, bionic design, system optimization, simulation verification

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.

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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

Battlefield target intelligence system architecture modeling and system optimization

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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 [14–16]	Automatic target recognition and positioning processing technology [17–20]	−
Intelligence fusion function	Intelligence information automatic fusion technology [21–23]	−	−
Intelligence distribution function	Intelligent distribution technology [24,25]	−	−
Information interaction function	New generation data link technology [26–30]	−	−
Security and confidentiality function	Blockchain technology [31–34]	General computing platform localization technology [35,36]	−
Command and control function	Intelligent intelligence staff technology [37–41]	Unmanned platform collaborative command and control technology [42–47]	−
Information system computing architecture	Cloud computing technology [48–51]	Edge computing technology [52–55]	Fog computing technology [56–58]