Ultra-wideband Radar for Human Respiratory Motion Detection and Estimation
Date Issued
2012
Date
2012
Author(s)
Chen, Tsung-Cheng
Abstract
The purpose of this research is to use Ultra-wideband (UWB) Radar for human respiratory motion detection and the main contributions of this study are the design of UWB radar signal processing algorithms as well as its system implementation. Prior researches in the literature on the use of UWB radars for human respiratory motion detection are mainly based on cross-correlation functions or spectrum analysis. These methods typically require high sampling frequency and often only capable of 1D measurements. In this study, the auto-correlation function is used instead in order to achieve higher resolution and alleviate the limitation on the sampling rate. The estimation error of the breathing rate is 8%. In addition, the synthetic aperture technique is also used for 2D imaging. Two methods, including the phase-correction method and the generalized coherence factor method, have been applied for image quality improvements. And it was found that the combination of the two methods can reduce the mainlobe width to 40% of its original width and reduce the sidelobe level by 20dB. Finally, an algorithm that combines the synthetic aperture technique and human respiratory motion detection was proposed. The algorithm makes use of the generalized incoherence factor (GICF), and the value of GICF increases at the region where there is human respiratory motion. In addition, the respiratory motion rate is estimated by defining filter bank based GCF (FBGCF). The image intensity at regions with and without breathing human has a ratio of 33 (30dB). And for the FBGCF method, the ratio of the energy at the filter that corresponds to human respiratory motion and the energies at the other filters is 8 (18dB).
Subjects
UWB synthetic aperture radar
human respiratory motion detection
auto-correlation method
phase-correction method
generalized coherence factor based adaptive imaging method
generalized incoherence factor (GICF)
filter bank based GCF (FBGCF)
Type
thesis
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