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Kernel Principal Component Analysis for UWB-Based Ranging
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-7599-4367
University of Gävle, Sweden.
Swedish Defense Research Agency (FOI), Linköping, Sweden.
2014 (English)In: IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2014, 2014, 145-149 p.Conference paper, Published paper (Refereed)
Abstract [en]

Accurate positioning in harsh environments can enable many application, such as search-and-rescue in emergency situations. For this problem, ultra-wideband (UWB) technology can provide the most accurate range estimates, which are required for range-based positioning. However, it still faces a problem in non-line-of-sight (NLOS) environments, in which range estimates based on time-of-arrival (TOA) are positively biased. There are many techniques that try to address this problem, mainly based on NLOS identification and NLOS error mitigation. However, these techniques do not exploit all available information from the UWB channel impulse response. In this paper, we propose a novel ranging technique based on kernel principal component analysis (kPCA), in which the selected channel parameters are projected onto nonlinear orthogonal high-dimensional space, and a subset of these projections is then used for ranging. We tested this technique using UWB measurements obtained in a basement tunnel of Linkoping university, and found that it provides much better ranging performance comparing with standard techniques based on PCA and TOA.

Place, publisher, year, edition, pages
2014. 145-149 p.
Series
IEEE International Workshop on Signal Processing Advances in Wireless Communications, ISSN 2325-3789
Keyword [en]
ranging, ultra-wideband, time-of-arrival, kernel principal component analysis, machine learning
National Category
Communication Systems Signal Processing
Identifiers
URN: urn:nbn:se:liu:diva-106648DOI: 10.1109/SPAWC.2014.6941337ISI: 000348859000030ISBN: 978-1-4799-4903-8 (print)OAI: oai:DiVA.org:liu-106648DiVA: diva2:717719
Conference
15th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2014), 22-25 June 2014, Toronto, Canada
Projects
COOPLOC
Funder
Swedish Foundation for Strategic Research eLLIIT - The Linköping‐Lund Initiative on IT and Mobile Communications
Available from: 2014-05-16 Created: 2014-05-16 Last updated: 2016-08-31

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Savic, VladimirLarsson, Erik G.Stenumgaard, Peter
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