Citation

Bakhuraisa, Yaser A. and Lim, Heng Siong and Chan, Yee Kit and Hilman, Muhammad (2025) UAV-Assisted Localization of Ground Nodes in Urban Environments Using Path Loss Measurements. Drones, 9 (6). p. 450. ISSN 2504-446X

Text UAV-Assisted Localization of Ground Nodes in Urban Environments Using Path Loss Measurements.pdf - Published Version Restricted to Repository staff only Download (2MB)

Abstract

This paper proposes a distance estimation error reduction framework to improve ground node localization accuracy in urban environments using an unmanned aerial vehicle (UAV) and path loss measurements. The primary goal of the framework is to bound distance estimation errors arising from inherent inaccuracies in path loss measurements. A k-means clustering algorithm is first applied to identify the region in which the ground node is located. Then, an analytical approach is used to select UAV waypoints. Moreover, a mean-based exponential smoothing approach is employed to refine the path loss measurements of the selected waypoints to mitigate the effects of multipath components that introduce significant errors in distance estimation. Finally, two estimators, maximum likelihood (ML)-based and semidefinite programming (SDP)-based relaxation, are employed to estimate the ground node’s location, validating the effectiveness of the proposed framework. Evaluations using ray tracing simulation data demonstrate a notable improvement in localization accuracy. The proposed framework effectively bounds the distance estimation errors and significantly reduces overall localization errors compared to conventional unbounded methods. Moreover, both estimators with the proposed framework achieve comparable localization accuracy, highlighting the framework’s capability to address key challenges in ML-based localization.

Item Type:	Article
Uncontrolled Keywords:	Localization
Subjects:	Q Science > QP Physiology > QP351 Neurophysiology and Neuropsychology
Divisions:	Faculty of Engineering and Technology (FET)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	29 Jul 2025 06:24
Last Modified:	01 Aug 2025 04:41
URII:	http://shdl.mmu.edu.my/id/eprint/14400

Downloads

Edit (login required)