Research on Recognition Method of Maneuver and Formation Tactics in BVR Cooperative Combat Based on Dynamic Bayesian Network

Yan Zhang; Yuyang Liu; Yinjing Guo; Xiaodong Wang; Lei Feng; Guo Li; Yangming Guo

doi:10.1007/978-981-19-3387-5_163

Research on Recognition Method of Maneuver and Formation Tactics in BVR Cooperative Combat Based on Dynamic Bayesian Network

Yan Zhang, Yuyang Liu, Yinjing Guo, Xiaodong Wang, Lei Feng, Guo Li, Yangming Guo

School of Cybersecurity

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

With breakthroughs in modern weaponry and equipment technology and coordinated formation flying, coordinated operations beyond visual range have become the main form of modern air combat. Accurately identifying enemy maneuvers and formation tactics is of great significance for grasping the dominance of the battlefield and grasping the direction of war. Traditional situation assessment research lacks pertinence to coordinated formation tactics and strategies in the BVR battlefield. This paper considers the influence of the characteristics of BVR fighters on tactical strategies, analyzes the causal relationship between the characteristics of flight parameters and the evolution of tactical movements, and constructs a dynamic Recognition model of typical maneuver movements beyond the visual range based on Bayesian network; on this basis, a recognition model of cooperative formation tactics is constructed. Finally, simulation experiments verify the accuracy and effectiveness of the model’s recognition. Further, this model can be used as a threat module of the beyond-horizon cooperative formation tactics for the Air combat situation assessment.

Original language	English
Title of host publication	Signal and Information Processing, Networking and Computers - Proceedings of the 8th International Conference on Signal and Information Processing, Networking and Computers, ICSINC 2021
Editors	Jiande Sun, Yue Wang, Mengyao Huo, Lexi Xu
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	1365-1375
Number of pages	11
ISBN (Print)	9789811933868
DOIs	https://doi.org/10.1007/978-981-19-3387-5_163
State	Published - 2023
Event	8th International Conference on Signal and Information Processing, Network and Computers, ICSINC 2021 - Shandong, China Duration: 13 Sep 2021 → 17 Sep 2021

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	917 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	8th International Conference on Signal and Information Processing, Network and Computers, ICSINC 2021
Country/Territory	China
City	Shandong
Period	13/09/21 → 17/09/21

Keywords

Bayesian network
Cloud model
Coordinated operations of beyond visual range
Maneuver recognition
Tactical identification

Access to Document

10.1007/978-981-19-3387-5_163

Cite this

Zhang, Y., Liu, Y., Guo, Y., Wang, X., Feng, L., Li, G., & Guo, Y. (2023). Research on Recognition Method of Maneuver and Formation Tactics in BVR Cooperative Combat Based on Dynamic Bayesian Network. In J. Sun, Y. Wang, M. Huo, & L. Xu (Eds.), Signal and Information Processing, Networking and Computers - Proceedings of the 8th International Conference on Signal and Information Processing, Networking and Computers, ICSINC 2021 (pp. 1365-1375). (Lecture Notes in Electrical Engineering; Vol. 917 LNEE). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-19-3387-5_163

Zhang, Yan ; Liu, Yuyang ; Guo, Yinjing et al. / Research on Recognition Method of Maneuver and Formation Tactics in BVR Cooperative Combat Based on Dynamic Bayesian Network. Signal and Information Processing, Networking and Computers - Proceedings of the 8th International Conference on Signal and Information Processing, Networking and Computers, ICSINC 2021. editor / Jiande Sun ; Yue Wang ; Mengyao Huo ; Lexi Xu. Springer Science and Business Media Deutschland GmbH, 2023. pp. 1365-1375 (Lecture Notes in Electrical Engineering).

@inproceedings{4fe633532aca483c8675125d0dee8abb,

title = "Research on Recognition Method of Maneuver and Formation Tactics in BVR Cooperative Combat Based on Dynamic Bayesian Network",

abstract = "With breakthroughs in modern weaponry and equipment technology and coordinated formation flying, coordinated operations beyond visual range have become the main form of modern air combat. Accurately identifying enemy maneuvers and formation tactics is of great significance for grasping the dominance of the battlefield and grasping the direction of war. Traditional situation assessment research lacks pertinence to coordinated formation tactics and strategies in the BVR battlefield. This paper considers the influence of the characteristics of BVR fighters on tactical strategies, analyzes the causal relationship between the characteristics of flight parameters and the evolution of tactical movements, and constructs a dynamic Recognition model of typical maneuver movements beyond the visual range based on Bayesian network; on this basis, a recognition model of cooperative formation tactics is constructed. Finally, simulation experiments verify the accuracy and effectiveness of the model{\textquoteright}s recognition. Further, this model can be used as a threat module of the beyond-horizon cooperative formation tactics for the Air combat situation assessment.",

keywords = "Bayesian network, Cloud model, Coordinated operations of beyond visual range, Maneuver recognition, Tactical identification",

author = "Yan Zhang and Yuyang Liu and Yinjing Guo and Xiaodong Wang and Lei Feng and Guo Li and Yangming Guo",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 8th International Conference on Signal and Information Processing, Network and Computers, ICSINC 2021 ; Conference date: 13-09-2021 Through 17-09-2021",

year = "2023",

doi = "10.1007/978-981-19-3387-5_163",

language = "英语",

isbn = "9789811933868",

series = "Lecture Notes in Electrical Engineering",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "1365--1375",

editor = "Jiande Sun and Yue Wang and Mengyao Huo and Lexi Xu",

booktitle = "Signal and Information Processing, Networking and Computers - Proceedings of the 8th International Conference on Signal and Information Processing, Networking and Computers, ICSINC 2021",

}

Zhang, Y, Liu, Y, Guo, Y, Wang, X, Feng, L, Li, G & Guo, Y 2023, Research on Recognition Method of Maneuver and Formation Tactics in BVR Cooperative Combat Based on Dynamic Bayesian Network. in J Sun, Y Wang, M Huo & L Xu (eds), Signal and Information Processing, Networking and Computers - Proceedings of the 8th International Conference on Signal and Information Processing, Networking and Computers, ICSINC 2021. Lecture Notes in Electrical Engineering, vol. 917 LNEE, Springer Science and Business Media Deutschland GmbH, pp. 1365-1375, 8th International Conference on Signal and Information Processing, Network and Computers, ICSINC 2021, Shandong, China, 13/09/21. https://doi.org/10.1007/978-981-19-3387-5_163

Research on Recognition Method of Maneuver and Formation Tactics in BVR Cooperative Combat Based on Dynamic Bayesian Network. / Zhang, Yan; Liu, Yuyang; Guo, Yinjing et al.
Signal and Information Processing, Networking and Computers - Proceedings of the 8th International Conference on Signal and Information Processing, Networking and Computers, ICSINC 2021. ed. / Jiande Sun; Yue Wang; Mengyao Huo; Lexi Xu. Springer Science and Business Media Deutschland GmbH, 2023. p. 1365-1375 (Lecture Notes in Electrical Engineering; Vol. 917 LNEE).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Research on Recognition Method of Maneuver and Formation Tactics in BVR Cooperative Combat Based on Dynamic Bayesian Network

AU - Zhang, Yan

AU - Liu, Yuyang

AU - Guo, Yinjing

AU - Wang, Xiaodong

AU - Feng, Lei

AU - Li, Guo

AU - Guo, Yangming

PY - 2023

Y1 - 2023

N2 - With breakthroughs in modern weaponry and equipment technology and coordinated formation flying, coordinated operations beyond visual range have become the main form of modern air combat. Accurately identifying enemy maneuvers and formation tactics is of great significance for grasping the dominance of the battlefield and grasping the direction of war. Traditional situation assessment research lacks pertinence to coordinated formation tactics and strategies in the BVR battlefield. This paper considers the influence of the characteristics of BVR fighters on tactical strategies, analyzes the causal relationship between the characteristics of flight parameters and the evolution of tactical movements, and constructs a dynamic Recognition model of typical maneuver movements beyond the visual range based on Bayesian network; on this basis, a recognition model of cooperative formation tactics is constructed. Finally, simulation experiments verify the accuracy and effectiveness of the model’s recognition. Further, this model can be used as a threat module of the beyond-horizon cooperative formation tactics for the Air combat situation assessment.

AB - With breakthroughs in modern weaponry and equipment technology and coordinated formation flying, coordinated operations beyond visual range have become the main form of modern air combat. Accurately identifying enemy maneuvers and formation tactics is of great significance for grasping the dominance of the battlefield and grasping the direction of war. Traditional situation assessment research lacks pertinence to coordinated formation tactics and strategies in the BVR battlefield. This paper considers the influence of the characteristics of BVR fighters on tactical strategies, analyzes the causal relationship between the characteristics of flight parameters and the evolution of tactical movements, and constructs a dynamic Recognition model of typical maneuver movements beyond the visual range based on Bayesian network; on this basis, a recognition model of cooperative formation tactics is constructed. Finally, simulation experiments verify the accuracy and effectiveness of the model’s recognition. Further, this model can be used as a threat module of the beyond-horizon cooperative formation tactics for the Air combat situation assessment.

KW - Bayesian network

KW - Cloud model

KW - Coordinated operations of beyond visual range

KW - Maneuver recognition

KW - Tactical identification

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U2 - 10.1007/978-981-19-3387-5_163

DO - 10.1007/978-981-19-3387-5_163

M3 - 会议稿件

AN - SCOPUS:85135006409

SN - 9789811933868

T3 - Lecture Notes in Electrical Engineering

SP - 1365

EP - 1375

BT - Signal and Information Processing, Networking and Computers - Proceedings of the 8th International Conference on Signal and Information Processing, Networking and Computers, ICSINC 2021

A2 - Sun, Jiande

A2 - Wang, Yue

A2 - Huo, Mengyao

A2 - Xu, Lexi

PB - Springer Science and Business Media Deutschland GmbH

T2 - 8th International Conference on Signal and Information Processing, Network and Computers, ICSINC 2021

Y2 - 13 September 2021 through 17 September 2021

ER -

Zhang Y, Liu Y, Guo Y, Wang X, Feng L, Li G et al. Research on Recognition Method of Maneuver and Formation Tactics in BVR Cooperative Combat Based on Dynamic Bayesian Network. In Sun J, Wang Y, Huo M, Xu L, editors, Signal and Information Processing, Networking and Computers - Proceedings of the 8th International Conference on Signal and Information Processing, Networking and Computers, ICSINC 2021. Springer Science and Business Media Deutschland GmbH. 2023. p. 1365-1375. (Lecture Notes in Electrical Engineering). doi: 10.1007/978-981-19-3387-5_163

Research on Recognition Method of Maneuver and Formation Tactics in BVR Cooperative Combat Based on Dynamic Bayesian Network

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