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Optimization of Distributed UAV Swarm Placement for Target Localization Using Multiple Heuristic Algorithms Based on Compressive Sensing
- 1 School of Electronic and Information Engineering, Tongji University, Shanghai, China
- 2 School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China
- 3 College of Electrical and Electronic Information, XiHua University, Sichuan, China
- 4 Department of Electronic Information Engineering, Shenzhen University, Shenzhen, China
- 5 High School Affiliated to South China Normal University International Department, Guangzhou, China
* Author to whom correspondence should be addressed.
Abstract
Collaborative UAV swarms are increasingly deployed as temporary base stations in emergency situations to relay communications. This paper designs intelligent optimization algorithms, which minimizing mutual coherence within a region of interest (ROI) aims to solving challenge in these scenarios is optimizing the UAVs' locations to avoid mutual signal interference and ensure high communication quality. Minimizing mutual coherence reduces the likelihood of signal interference between UAVs. We explore various optimize algorithum, including Heuristic Search (HS) and Ant Colony Optimization (ACO) and so on. The results provide insights into each algorithm's performance in dynamic environments, helping to identify the most suitable approaches for UAV deployment in emergency scenarios. This study contributes to the development of efficient UAV deployment strategies, enhancing the reliability of UAV-based communication systems during critical events.
Keywords
UAV swarms, Optimize algorithum, mutual coherence, MIMO radar system
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Cite this article
Du,Z.;Liu,L.;Zhou,H.;Chen,Z.;Yao,Y. (2025). Optimization of Distributed UAV Swarm Placement for Target Localization Using Multiple Heuristic Algorithms Based on Compressive Sensing. Applied and Computational Engineering,132,43-54.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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