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Volume 11
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10.3390/electronics11020184
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Article

Distributed Cooperative Jamming with Neighborhood Selection Strategy for Unmanned Aerial Vehicle Swarms

by
Yongkun Zhou
1,
Dan Song
2,
Bowen Ding
1,
Bin Rao
1,
Man Su
3 and
Wei Wang
1,*
1
The School of Electronics and Communication Engineering, Sun Yat-Sen University, Guangzhou 510000, China
2
The Colloege of Information and Communication, National Uinversity of Defense Technology, Xi’an 710000, China
3
The Beijing Institute of Tracking and Telecommunication Technology, Beijing 100000, China
*
Author to whom correspondence should be addressed.
Electronics 2022, 11(2), 184; https://doi.org/10.3390/electronics11020184
Submission received: 22 November 2021 / Revised: 29 December 2021 / Accepted: 1 January 2022 / Published: 7 January 2022
(This article belongs to the Special Issue Advances in Swarm Intelligence, Data Science and Their Applications)
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Abstract

In system science, a swarm possesses certain characteristics which the isolated parts and the sum do not have. In order to explore emergence mechanism of a large–scale electromagnetic agents (EAs), a neighborhood selection (NS) strategy–based electromagnetic agent cellular automata (EA–CA) model is proposed in this paper. The model describes the process of agent state transition, in which a neighbor with the smallest state difference in each sector area is selected for state transition. Meanwhile, the evolution rules of the traditional CA are improved, and performance of different evolution strategies are compared. An application scenario in which the emergence of multi–jammers suppresses the radar radiation source is designed to demonstrate the effect of the EA–CA model. Experimental results show that the convergence speed of NS strategy is better than those of the traditional CA evolution rules, and the system achieves effective jamming with the target after emergence. It verifies the effectiveness and prospects of the proposed model in the application of electronic countermeasures (ECM).
Keywords: unmanned aerial vehicle (UAV); electromagnetic agent cellular automata (EA–CA) model; neighborhood selection (NS); electronic countermeasures (ECM) unmanned aerial vehicle (UAV); electromagnetic agent cellular automata (EA–CA) model; neighborhood selection (NS); electronic countermeasures (ECM)

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MDPI and ACS Style

Zhou, Y.; Song, D.; Ding, B.; Rao, B.; Su, M.; Wang, W. Distributed Cooperative Jamming with Neighborhood Selection Strategy for Unmanned Aerial Vehicle Swarms. Electronics 2022, 11, 184. https://doi.org/10.3390/electronics11020184

AMA Style

Zhou Y, Song D, Ding B, Rao B, Su M, Wang W. Distributed Cooperative Jamming with Neighborhood Selection Strategy for Unmanned Aerial Vehicle Swarms. Electronics. 2022; 11(2):184. https://doi.org/10.3390/electronics11020184

Chicago/Turabian Style

Zhou, Yongkun, Dan Song, Bowen Ding, Bin Rao, Man Su, and Wei Wang. 2022. "Distributed Cooperative Jamming with Neighborhood Selection Strategy for Unmanned Aerial Vehicle Swarms" Electronics 11, no. 2: 184. https://doi.org/10.3390/electronics11020184

APA Style

Zhou, Y., Song, D., Ding, B., Rao, B., Su, M., & Wang, W. (2022). Distributed Cooperative Jamming with Neighborhood Selection Strategy for Unmanned Aerial Vehicle Swarms. Electronics, 11(2), 184. https://doi.org/10.3390/electronics11020184

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