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 language | English |
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Title of host publication | Proceedings of IEEE 16th International Conference on Dependable, Autonomic and Secure Computing |
Publisher | IEEE |
Pages | 467-473 |
Number of pages | 7 |
ISBN (Print) | 9781538675182 |
DOIs | |
Publication status | Published - Aug 2018 |
Event | IEEE 16th International Conference on Dependable, Autonomic and Secure Computing - Athens, Greece Duration: 12 Aug 2018 → 15 Aug 2018 |
Conference
Conference | IEEE 16th International Conference on Dependable, Autonomic and Secure Computing |
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Abbreviated title | DASC-PICom-DataCom-CyberSciTec 2018 |
Country/Territory | Greece |
City | Athens |
Period | 12/08/18 → 15/08/18 |