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dRTI: Directional Radio Tomographic Imaging
RISE, Swedish ICT, SICS. University of New South Wales, Australia; CSIRO Commonwealth Scientific and Industrial Research Organisation.
Uppsala University, Sweden.
University of Utah, US; Xandem Technology, USA.
University of New South Wales, Australia; CSIRO Commonwealth Scientific and Industrial Research Organisation.
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2015 (English)In: Proceedings of the 14th International Conference on Information Processing in Sensor Networks (IPSN '15), 2015, 8, p. 166-177Conference paper, Published paper (Refereed)
Abstract [en]

Radio tomographic imaging (RTI) enables device free localisation of people and objects in many challenging environments and situations. Its basic principle is to detect the changes in the statistics of radio signals due to the radio link obstruction by people or objects. However, the localisation accuracy of RTI suffers from complicated multipath propagation behaviours in radio links. We propose to use inexpensive and energy efficient electronically switched directional (ESD) antennas to improve the quality of radio link behaviour observations, and therefore, the localisation accuracy of RTI. We implement a directional RTI (dRTI) system to understand how directional antennas can be used to improve RTI localisation accuracy. We also study the impact of the choice of antenna directions on the localisation accuracy of dRTI and propose methods to effectively choose informative antenna directions to improve localisation accuracy while reducing overhead. Furthermore, we analyse radio link obstruction performance in both theory and simulation, as well as false positives and false negatives of the obstruction measurements to show the superiority of the directional communication for RTI. We evaluate the performance of dRTI in diverse indoor environments and show that dRTI significantly outperforms the existing RTI localisation methods based on omni-directional antennas.

Place, publisher, year, edition, pages
2015, 8. p. 166-177
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:ri:diva-24512DOI: 10.1145/2737095.2737118Scopus ID: 2-s2.0-84954135642ISBN: 978-1-4503-3475-4 (print)OAI: oai:DiVA.org:ri-24512DiVA, id: diva2:1043596
Conference
14th International Symposium on Information Processing in Sensor Networks (IPSN 2015), April 13-16, Seattle, US
Available from: 2016-10-31 Created: 2016-10-31 Last updated: 2019-08-07Bibliographically approved

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Voigt, Thiemo

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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  • vancouver
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  • en-US
  • fi-FI
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  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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