Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6842
Title: Hyperbolically-Warped Cepstral Coefficients for Improved Micro-Doppler Classification
Authors: Erol, Barış
Gürbüz, Sevgi Zübeyde
Keywords: micro-Doppler classification
cepstral features
mel-frequency cepstral coefficients (MFCC)
Issue Date: 2016
Publisher: IEEE
Source: IEEE Radar Conference (RadarConf) -- MAY 02-06, 2016 -- Philadelphia, PA
Series/Report no.: IEEE Radar Conference
Abstract: Mel-frequency cepstrum coefficients (MFCC) have been used in many recent works as features for micro-Doppler classification. Originally proposed as features for speech recognition, the filter bank applied as part of the computation of the MFCC is designed with spacing according to the mel-frequency scale - a scale based upon the auditory properties of the human ear. However, the frequency composition of micro-Doppler signatures is completely unrelated to the mel-frequency scale. In this work, an alternative set of features computed using a filter bank based on a hyperbolically-warped frequency scale is proposed. A 21.25% increase in the correct classification rate of running, walking, creeping, and crawling is obtained when the proposed hyperbolically-warped cepstral coefficients (HWCC) are used as opposed to MFCC.
URI: https://hdl.handle.net/20.500.11851/6842
ISBN: 978-1-5090-0863-6
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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