Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/29
Title: Wavelet Based Denoising of the Simulated Chest Wall Motion Detected by SFCW Radar
Authors: Acar, Yunus Emre
Şeflek, İbrahim
Yaldız, Ercan
Issue Date: 2019
Publisher: LGEP-SUPELEC
Abstract: Low power and compact radars have emerged with the development of electronic technology. This has enabled the use of radars in indoor environments and the realization of many applications. The detection, tracking and classification of human movements by radar are among the remarkable applications. Contactless detection of human vital signs improves the quality of life of patients being kept under observation and facilitates the work of experts. In this study, it was simulated that the movement of the chest wall was modeled and detected by the SFCW radar. Gaussian, Rician and uniformly distributed random noise types were added to the modeled chest motion at different levels. The noisy signal obtained at the receiver is denoised with different mother wavelet functions and the performances of these functions are presented comparatively.
URI: https://hdl.handle.net/20.500.13091/29
ISSN: 2119-0275
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

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