Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/7044
Title: Micro-Doppler-Based Human Activity Classification Using the Mote-Scale BumbleBee Radar
Authors: Çağlıyan, Bahri
Gürbüz, Sevgi Zübeyde
Keywords: Classification
human activity recognition
human micro-doppler
wireless radar networks (WSNs)
Issue Date: 2015
Publisher: IEEE-Inst Electrical Electronics Engineers Inc
Abstract: Human activity recognition is an emerging technology formany security, surveillance, and health service applications utilizing wireless sensor networks (WSNs). However, the exploitation of radar in WSNs has been only recently made possible through the development of small, low-power, and low-cost wireless radar motes, such as the BumbleBee radar developed by the Samraksh Company. This letter explores the capacity of using the BumbleBee radar for indoor human activity classification based on micro-Doppler signatures. The electromagnetic measurements of the signal transmitted by the BumbleBee radar are made to fully characterize the sensor and its limitations. A database of the multiperspective micro-Doppler signatures measured from the BumbleBee radar is compiled to analyze the classification performance and limitations due to the dwell time and the aspect angle. Within the operational constraints delineated, it is shown that the BumbleBee radar can be used to discriminate between walking, running, and crawling, even under variable conditions.
URI: https://doi.org/10.1109/LGRS.2015.2452946
https://hdl.handle.net/20.500.11851/7044
ISSN: 1545-598X
1558-0571
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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