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The Extraction of Micro-Doppler Features from Human Motions
Date
2014-04-25
Author
Alemdaroglu, Ozge Topuz
Candan, Çağatay
Koç, Seyit Sencer
Metadata
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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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This study aims to experimentally investigate the feasibility of discriminating human motions with the help of micro-Doppler features by using radar. In the first phase of the work, the synthetic data is generated through the human walking simulator by V. Chen and different time-frequency transformations are applied on the data. In the following phase, several field experiments are conducted and the experimental data for running, crawling, creeping and walking with the aspect angles of 0 degrees, 30 degrees, 60 degrees are collected and spectrograms are obtained. Lastly, six features, which are torso frequency, bandwidth of the signal, offset of the signal, bandwidth without micro-Dopplers, the standard deviation of the signal strength, the period of the arms or legs motions are extracted from the spectrograms and the efficiencies of the features in motion classification are compared.
Subject Keywords
Micro-Doppler
,
Human Motion Classification
,
Feature Extraction
URI
https://hdl.handle.net/11511/55742
Conference Name
22nd IEEE Signal Processing and Communications Applications Conference (SIU)
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
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O. T. Alemdaroglu, Ç. Candan, and S. S. Koç, “The Extraction of Micro-Doppler Features from Human Motions,” presented at the 22nd IEEE Signal Processing and Communications Applications Conference (SIU), Karadeniz Teknik Univ, Trabzon, TURKEY, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/55742.