Evaluation of vulnerability of MAV/UAV collaborative combat network based on complex network

Shulan Yang, Zhiwei Hou and Hongbo Chen

Chaos, Solitons & Fractals, 2023, vol. 172, issue C

Abstract: In recent years, the Manned/Unmanned Aerial Vehicle (MAV/UAV) collaborative combat mode has become an important mode. Therefore, it is important to assess the vulnerability of Manned/Unmanned Aerial Vehicle Collaborative Combat Networks (MUCNs). In this paper, we analyze the meaning of nodes and edges of MUCNs, propose five vulnerability indicators, and construct a vulnerability indicator system of MUCNs. In addition, the network contribution method is proposed to aggregate the vulnerability indicators of MUCNs. Finally, through simulation, the effectiveness of the network contribution method is demonstrated by comparing and analyzing with three commonly used indicator aggregation methods. This paper can provide a reference for designing MUCNs with lower vulnerability and a vulnerability evaluation method for the development of MAV/UAV collaborative combat strategies.

Keywords: MAV/UAV collaborative combat network; Vulnerability indicator system; Network contribution method (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:172:y:2023:i:c:s0960077923004010

DOI: 10.1016/j.chaos.2023.113500

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