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On Mitigation of Ranging Errors for Through-The-Body NLOS Conditions using Convolutional Neural Networks
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Publication Year
2021-02-07
Journal
International Conference on Advanced Communication Technology, ICACT
Publisher
Institute of Electrical and Electronics Engineers Inc.
Citation
International Conference on Advanced Communication Technology, ICACT, Vol.2021-February, pp.141-144
Keyword
Convolutional Neural NetworksHuman Body NLOSNLOS MitigationRanging ErrorUltrawideband (UWB)
Mesh Keyword
High-precisionHuman bodiesIndoor localizationLocation-aware applicationNLOS conditionsNonline of sightRanging error mitigationsRanging errors
All Science Classification Codes (ASJC)
Electrical and Electronic Engineering
Abstract
A UWB-based indoor localization is highly useful in various location-Aware applications due to its high-precision and robustness in obstacles. However, it is still a challenging issue to mitigate ranging errors caused by non-line-of-sight(NLOS) conditions. In recent years, various approaches have been attempted using deep learning, but this is mostly the study of NLOS conditions by indoor obstacles. In this paper, we proposed a solution of ranging error mitigation for through-The-human body NLOS conditions using Convolutional Neural Networks.
ISSN
1738-9445
Language
eng
URI
https://aurora.ajou.ac.kr/handle/2018.oak/36722
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85102851265&origin=inward
DOI
https://doi.org/10.23919/icact51234.2021.9370584
Journal URL
http://www.ieee.org
Type
Conference
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Ko, Young-Bae Image
Ko, Young-Bae고영배
Department of Software and Computer Engineering
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