Opportunistic Doppler-Only Indoor localization via Passive Radar

Wenda Li, Bo Tan, Robert Piechocki

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

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Abstract

Indoor localization is a vital ingredient for many e-Healthcare and Ambient Assisted Living (AAL) applications. However, accurate, low power and user acceptable solutions remain elusive. In this paper, we present a novel opportunistic system which estimates the localization information based only on the Doppler information from the user. The Doppler information is collected using the passive radar technique that deploys the RF energy transfer signal which originally intended only to deliver energy to home IoT devices. A low complexity Extended Kalman Filter (EKF) is also proposed to predict and track the user's location. A real-time system has been built based on the software defined radio (SDR) platform to verify the proposed methodology.
Experimental results indicate that the proposed concepts can be used for indoor localization with a high degree of accuracy.
Original languageEnglish
Title of host publication 2018 IEEE 16th Intl Conf on Dependable, Autonomic and Secure Computing, 16th Intl Conf on Pervasive Intelligence and Computing, 4th Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech)
PublisherIEEE
Pages467-473
Number of pages7
ISBN (Electronic)978-1-5386-7518-2
DOIs
Publication statusPublished - 29 Oct 2018
EventThe 3rd IEEE Cyber Science and Technology Congress - Athens, Athens, Greece
Duration: 12 Aug 201815 Aug 2018
http://cyber-science.org/2018/

Conference

ConferenceThe 3rd IEEE Cyber Science and Technology Congress
CountryGreece
CityAthens
Period12/08/1815/08/18
Internet address

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Keywords

  • Passive radar
  • Complexity theory
  • Radar tracking
  • Doppler shift
  • Surveillance
  • Receivers

Cite this

Li, W., Tan, B., & Piechocki, R. (2018). Opportunistic Doppler-Only Indoor localization via Passive Radar. In 2018 IEEE 16th Intl Conf on Dependable, Autonomic and Secure Computing, 16th Intl Conf on Pervasive Intelligence and Computing, 4th Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech) (pp. 467-473). IEEE. https://doi.org/10.1109/DASC/PiCom/DataCom/CyberSciTec.2018.00093