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mmRTI: Radio Tomographic Imaging using Highly-Directional Millimeter-Wave Devices for Accurate and Robust Indoor Localization
KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS.
2018 (English)In: IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC, Institute of Electrical and Electronics Engineers Inc. , 2018, p. 1-7Conference paper, Published paper (Refereed)
Abstract [en]

As a device-free approach, radio tomographic imaging (RTI) is ideally suited for low-cost indoor localization in context-aware Internet-of-Things applications. However, the fundamental RTI algorithm relies on shadowing of the line of sight (LOS) links and therefore, conventional RTI implementations using 2.4 GHz sensing networks (microRTI) fail to accurately localize users in multipath-rich indoor environments. The localization accuracy is further degraded by external human movement that affects the signal propagation. In this paper, we propose mmRTI, a novel RTI approach based on a highly-directional, millimeter-wave sensing network, that aims to improve indoor localization by utilizing the LOS-dominant nature of millimeter-wave signal propagation. We experimentally evaluate mmRTI, operating at 60 GHz, with and without human movement around the sensing network, in two indoor environments, and compare its performance against the conventional microRTI approach. We observe that mmRTI achieves a 90%-ile localization error of 0.07 m-0.25m, an improvement of 2.41 m-2.60m compared to microRTI, while remaining unaffected by external human movement, which degrades the microRTI localization accuracy by up to 1.2 m. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2018. p. 1-7
Keywords [en]
Millimeter wave devices, Millimeter waves, Radio communication, Tomography, Indoor localization, Internet of things applications, Line-of-sight links, Localization accuracy, Localization errors, Millimeter wave sensing, Millimeter wave signals, Tomographic imaging, Indoor positioning systems
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-227433DOI: 10.1109/PIMRC.2017.8292523Scopus ID: 2-s2.0-85045269638ISBN: 9781538635315 OAI: oai:DiVA.org:kth-227433DiVA, id: diva2:1210447
Conference
28th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2017, 8 October 2017 through 13 October 2017
Note

Conference code: 134680; Export Date: 9 May 2018; Conference Paper. QC 20180528

Available from: 2018-05-28 Created: 2018-05-28 Last updated: 2018-05-28Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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Output format
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