Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6380
Title: Classification of Human Micro-Doppler in a Radar Network
Authors: Tekeli, Bürkan
Gürbüz, Sevgi Zübeyde
Yüksel, Melda
Gürbüz, Ali Cafer
Güldoğan, Mehmet Burak
Keywords: [No Keywords]
Issue Date: 2013
Publisher: IEEE
Source: IEEE Radar Conference (RADAR) -- APR 29-MAY 03, 2013 -- Ottawa, CANADA
Series/Report no.: IEEE Radar Conference
Abstract: The unique, bi-pedal motion of humans has been shown to generate a characteristic micro-Doppler signature in the time-frequency domain that can be used to discriminate humans from not just other targets, but also between different activities, such as walking and running. However, the classification performance increasingly drops as the aspect angle between the target and radar approaches perpendicular, and the radial velocity component seen by the radar is minimized. In this paper, exploitation of the multi-static micro-Doppler signature formed from multi-angle observations of a radar network is proposed to improve oblique-angle classification performance. The concept of mutual information is applied to find the order of importance of features for a given classification problem, thereby enabling the selection of optimal features prior to classification. Strategies for fusing multistatic data using mutual information and model-based approaches are discussed.
URI: https://hdl.handle.net/20.500.11851/6380
ISBN: 978-1-4673-5794-4; 978-1-4673-5792-0
ISSN: 1097-5764
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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