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A Localization Enhancement Method Based on Direct-Path Identification and Tracking for Future Networks

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Vydáno v:Sensors vol. 25, no. 15 (2025), p. 4538-4556
Hlavní autor: Huang, Yuhong
Další autoři: Zhao, Youping
Vydáno:
MDPI AG
Témata:
Propagation
Accuracy
Transmitters
Methods
Algorithms
Localization
Identification
Internet of Things
Neural networks
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Abstrakt:Localization is one of the essential problems in the Internet of Things (IoT). Dynamic changes in the radio environment may lead to poor localization accuracy or discontinuous localization in non-line-of-sight (NLOS) scenarios. To address this problem, this paper proposes a localization enhancement method based on direct-path identification and tracking. More specifically, the proposed method significantly reduces the range error and localization error by quickly identifying the line-of-sight (LOS) to NLOS transition and effectively tracking the direct path. In a large testing hall, localization experiments based on the ultra-wideband (UWB) signal have been carried out. Experimental results show that the proposed method achieves a root mean square localization error of less than 0.3 m along the user equipment (UE) movement trajectory with serious NLOS propagation conditions. Compared with conventional methods, the proposed method significantly improves localization accuracy while ensuring continuous localization.
ISSN:1424-8220
DOI:10.3390/s25154538
Zdroj:Health & Medical Collection