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Enabling Contactless Detection of Moving Humans with Dynamic Speeds Using CSI

Published:23 January 2018Publication History
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Abstract

Device-free passive detection is an emerging technology to detect whether there exist any moving entities in the areas of interest without attaching any device to them. It is an essential primitive for a broad range of applications including intrusion detection for safety precautions, patient monitoring in hospitals, child and elder care at home, and so forth. Despite the prevalent signal feature Received Signal Strength (RSS), most robust and reliable solutions resort to a finer-grained channel descriptor at the physical layer, e.g., the Channel State Information (CSI) in the 802.11n standard. Among a large body of emerging techniques, however, few of them have explored the full potential of CSI for human detection. Moreover, space diversity supported by nowadays popular multiantenna systems are not investigated to a comparable extent as frequency diversity. In this article, we propose a novel scheme for device-free PAssive Detection of moving humans with dynamic Speed (PADS). Both full information (amplitude and phase) of CSI and space diversity across multiantennas in MIMO systems are exploited to extract and shape sensitive metrics for accuracy and robust target detection. We prototype PADS on commercial WiFi devices, and experiment results in different scenarios demonstrate that PADS achieves great performance improvement in spite of dynamic human movements.

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      • Published in

        cover image ACM Transactions on Embedded Computing Systems
        ACM Transactions on Embedded Computing Systems  Volume 17, Issue 2
        Special Issue on MEMCODE 2015 and Regular Papers (Diamonds)
        March 2018
        640 pages
        ISSN:1539-9087
        EISSN:1558-3465
        DOI:10.1145/3160927
        Issue’s Table of Contents

        Copyright © 2018 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 23 January 2018
        • Accepted: 1 October 2017
        • Revised: 1 January 2017
        • Received: 1 December 2015
        Published in tecs Volume 17, Issue 2

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