A Fast Multi-UAV Assistance Positioning Architecture for Large-Scale Farming Operations

doi:10.1109/JIOT.2025.3584091

	A Fast Multi-UAV Assistance Positioning Architecture for Large-Scale Farming Operations
	Zhang, Jingyao 1,2; Chen, Haihua 1; Dai, Feng 1; Wang, Yancong 1; Li, Heyang 1; Zhang, Yucheng 1
	2025-09-15
发表期刊	IEEE INTERNET OF THINGS JOURNAL
ISSN	2327-4662
卷号	12 期号:18 页码:37645-37658
摘要	Autonomous intelligent agricultural vehicles significantly reduce labor requirements in large-scale farming operations. While real-time precise positioning of agricultural vehicles is prerequisite for autonomous operation, the global positioning system (GPS)-based positioning systems demonstrate insufficient accuracy in large-scale farming scenarios. Moreover, the limited infrastructure deployment and compromised network quality in extensive agricultural fields render conventional assistance positioning frameworks inadequate. Unmanned aerial vehicles (UAVs), as integral components of vehicular networks, facilitate positioning and navigation within spac-air-ground integrated networks (SAGINs). Based on this, this article proposes a multi-UAV rapid positioning assistance architecture for large-scale farming operations. Under this architecture, local area networks (LANs) are established between UAVs and agricultural vehicles, with each vehicle equipped with a uniform linear array (ULA). The system requires only signal transmission from UAVs, while the agricultural vehicles' local processing systems perform direction of arrival (DOA) estimation, followed by joint estimation to determine vehicle positioning coordinates. However, limited signal snapshots in practical DOA estimation environments compromise estimation accuracy. While compressed sensing (CS) algorithms demonstrate significant potential for DOA estimation applications, conventional CS methodologies employing uniform overcomplete dictionariess (UODs) in sparse representation phase incur substantial computational complexity. Additionally, the orthogonal matching pursuit (OMP) algorithm and its derivatives exhibit susceptibility to local optima convergence during signal reconstruction. Consequently, this article proposes the NODGA-CS model, integrating nonuniform overcomplete dictionary (NOD) with genetic algorithm (GA) optimization for enhanced CS-DOA estimation. Experimental results demonstrate that the proposed assistance architecture achieves superior positioning accuracy when benchmarked against state-of-the-art positioning frameworks.
关键词	Estimation Direction-of-arrival estimation Matching pursuit algorithms Computer architecture Accuracy Farming Autonomous aerial vehicles Genetic algorithms Dictionaries Signal reconstruction Assisted positioning architecture compressed sensing (CS) direction of arrival (DOA) genetic algorithm (GA) nonuniform overcomplete dictionary (NOD) unmanned aerial vehicles (UAVs)
DOI	10.1109/JIOT.2025.3584091
收录类别	SCI
语种	英语
资助项目	Strategic Priority Research Program of Chinese Academy of Sciences[XDA28120301] ; Natural Science Foundation of Shandong Province[ZR2021MF094] ; National Saline and Alkaline Land Comprehensive Utilization Technology Innovation Center Open Bidding for Selecting the Best Candidates[GYJ2023001] ; Science and Technology Specific Projects in Agricultural High-Tech Industrial Demonstration Area of the Yellow River Delta[2022SZX11] ; National Natural Science Foundation of China[42377037]
WOS研究方向	Computer Science ; Engineering ; Telecommunications
WOS类目	Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS记录号	WOS:001597451300046
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/41615
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Chen, Haihua
作者单位	1.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Jingyao,Chen, Haihua,Dai, Feng,et al. A Fast Multi-UAV Assistance Positioning Architecture for Large-Scale Farming Operations[J]. IEEE INTERNET OF THINGS JOURNAL,2025,12(18):37645-37658.
APA	Zhang, Jingyao,Chen, Haihua,Dai, Feng,Wang, Yancong,Li, Heyang,&Zhang, Yucheng.(2025).A Fast Multi-UAV Assistance Positioning Architecture for Large-Scale Farming Operations.IEEE INTERNET OF THINGS JOURNAL,12(18),37645-37658.
MLA	Zhang, Jingyao,et al."A Fast Multi-UAV Assistance Positioning Architecture for Large-Scale Farming Operations".IEEE INTERNET OF THINGS JOURNAL 12.18(2025):37645-37658.