Citation

Elngar, Ahmed M. A. A. and Lim, Heng Siong and Yee, Kit Chan and Bakhuraisa, Yaser Awadh and Wahidah, Ida (2026) Robust UAV localization of ground sensors in urban environments via path loss refinement and geometric selection. IAES International Journal of Artificial Intelligence (IJ-AI), 15 (1). p. 412. ISSN 2089-4872

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Abstract

Localizing ground sensors with unmanned aerial vehicles (UAVs) in dense urban environments is challenging because multipath and non-line-of-sight (NLoS) propagation distorts path loss (PL) measurements. This paper proposes a two-stage UAV localization framework that refines PL data and selects geometrically stable waypoint subsets before position estimation. In stage 1, PL samples are spatially smoothed by averaging measurements at neighboring UAV waypoints to reduce localized fluctuations. In stage 2, waypoint subsets are filtered using non-collinearity and non-adjacency constraints, and sensor positions are estimated using weighted least squares (WLS) and particle swarm optimization (PSO), with final estimates averaged across valid subsets. Wireless InSite ray-tracing simulations show that the framework reduces mean absolute error (MAE) from over 150 m to approximately 8.5 m. The proposed approach improves the practicality of UAV-assisted localization for urban internet of things (IoT) sensor deployments.

Item Type:	Article
Uncontrolled Keywords:	Geometric selection, Localization, Path loss, Unmanned aerial vehicles, Urban environment
Subjects:	T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL1-484 Motor vehicles. Cycles
Divisions:	Faculty of Engineering and Technology (FET)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	02 Apr 2026 04:31
Last Modified:	02 Apr 2026 04:31
URII:	http://shdl.mmu.edu.my/id/eprint/15654

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