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20 October 2023 Drone track planning method based on an improved ant colony algorithm for the task of measuring mobile signal strength
Zhigang Guo, Jialu Duan, Wenlei Zheng, Wei Yang
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Proceedings Volume 12916, Third International Conference on Signal Image Processing and Communication (ICSIPC 2023); 129160E (2023) https://doi.org/10.1117/12.3004647
Event: Third International Conference on Signal Image Processing and Communication (ICSIPC 2023), 2023, Kunming, China
Abstract
Mobile signal strength affects the deployment of IoT devices, and its distribution is often measured using UAVs designed reasonable routes and equipped with measuring equipment. Traditional ant colony algorithms used in track planning can easily fall into local optimal solutions and is not suitable for large-scale tasks, and an improved ant colony algorithm is proposed for solving the problem. The characteristic of the improved algorithm is that in the process of updating pheromones, an information release function that changes with the number of iterations is introduced to avoid falling into local optimal solutions. Additionally, optimized the pheromone volatility factor to enhance global search capability. Theoretical analysis and simulation experiments demonstrate that compared with traditional ant colony algorithms, the improved algorithm can not only quickly escape local optima, but also has stronger global search capabilities and certain robustness.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Zhigang Guo, Jialu Duan, Wenlei Zheng, and Wei Yang "Drone track planning method based on an improved ant colony algorithm for the task of measuring mobile signal strength", Proc. SPIE 12916, Third International Conference on Signal Image Processing and Communication (ICSIPC 2023), 129160E (20 October 2023); https://doi.org/10.1117/12.3004647
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KEYWORDS
Computer simulations
Algorithms
Mathematical optimization
Picosecond phenomena
Positive feedback
Unmanned aerial vehicles
Biomimetics
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