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.
Experimental results indicate that the proposed concepts can be used for indoor localization with a high degree of accuracy.
Original language | English |
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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) |
Publisher | IEEE |
Pages | 467-473 |
Number of pages | 7 |
ISBN (Electronic) | 978-1-5386-7518-2 |
DOIs | |
Publication status | Published - 29 Oct 2018 |
Event | The 3rd IEEE Cyber Science and Technology Congress - Athens, Athens, Greece Duration: 12 Aug 2018 → 15 Aug 2018 http://cyber-science.org/2018/ |
Conference
Conference | The 3rd IEEE Cyber Science and Technology Congress |
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Country/Territory | Greece |
City | Athens |
Period | 12/08/18 → 15/08/18 |
Internet address |
Bibliographical note
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Keywords
- Passive radar
- Complexity theory
- Radar tracking
- Doppler shift
- Surveillance
- Receivers