Opportunistic Doppler-Only Indoor localization via Passive Radar

Wenda Li, Bo Tan, Robert Piechocki

    Research output: Chapter in Book/Report/Conference proceedingConference proceedingpeer-review

    3 Citations (Scopus)
    167 Downloads (Pure)


    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)
    Number of pages7
    ISBN (Electronic)978-1-5386-7518-2
    Publication statusPublished - 29 Oct 2018
    EventThe 3rd IEEE Cyber Science and Technology Congress - Athens, Athens, Greece
    Duration: 12 Aug 201815 Aug 2018


    ConferenceThe 3rd IEEE Cyber Science and Technology Congress
    Internet address

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


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