Rapid reconnaissance of fixed targets on the ground by multiple UAVs

Kaiqi Yao; Bin Liu; Xianqiang Zhu

doi:10.1117/12.3029612

21 June 2024 Rapid reconnaissance of fixed targets on the ground by multiple UAVs

Kaiqi Yao, Bin Liu, Xianqiang Zhu

Proceedings Volume 13167, International Conference on Remote Sensing, Mapping, and Image Processing (RSMIP 2024); 131673A (2024) https://doi.org/10.1117/12.3029612
Event: International Conference on Remote Sensing, Mapping and Image Processing (RSMIP 2024), 2024, Xiamen, China

Abstract

UAV reconnaissance has many advantages, such as high reliability, strong flexibility and wide coverage. When using unmanned aerial vehicles to scout targets, it is often necessary to quickly scout many fixed targets. If it is obviously unreasonable to send one unmanned aerial vehicle for each target, it is also unreasonable to send one unmanned aerial vehicle to scout all targets. At the same time, we should also consider the actual needs, such as our own safety and the number of airport reconnaissance drones. Considering many factors, a fast reconnaissance model of multi-UAV fixed targets on the ground is established, and the minimum number of UAV sorties needed for reconnaissance of all targets is obtained by combining branch and bound method and modified combined optimization algorithm. The modified Dijkstra algorithm is used to determine the appropriate delivery point, which can meet the actual requirements of rapid reconnaissance in the battlefield, considering the factors such as air defense firepower range and transportation conditions. Finally, the feasibility of the model is verified by using simulation data, and the benefits and possible improvements of the model are analyzed.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Kaiqi Yao, Bin Liu, and Xianqiang Zhu "Rapid reconnaissance of fixed targets on the ground by multiple UAVs", Proc. SPIE 13167, International Conference on Remote Sensing, Mapping, and Image Processing (RSMIP 2024), 131673A (21 June 2024); https://doi.org/10.1117/12.3029612

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