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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
2022-01-01
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.2022-February, pp.141-144
Keyword
Convolutional Neural NetworksHuman Body NLOSNLOS MitigationRanging ErrorUltrawideband (UWB)
Mesh Keyword
ConditionConvolutional neural networkHuman bodiesHuman body non-line-of-sightIndoor localizationLocation-aware applicationNon-line-of-sight mitigationsNonline of sightRanging errorsUltrawideband
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/36850
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85127498808&origin=inward
DOI
https://doi.org/10.23919/icact53585.2022.9728942
Journal URL
http://www.ieee.org
Type
Conference
Funding
\This research was supported by the MIST(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW supervised by the IITP(Institute of Information & communications Technology Planning & Evaluation)\ (2015-0-00908)
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Ko, Young-Bae Image
Ko, Young-Bae고영배
Department of Software and Computer Engineering
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