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Abstract
This paper presents a new system for the detection of human respiration behind obstacles using impulse ultra-wideband (UWB) radar. In complex environments, low signal-to-noise ratios (SNRs) as they can result in significant errors in the respiration, heartbeat frequency, and range estimates. To improve the performance, the complex signal demodulation (CSD) technique is extended by employing the signal logarithm and derivative. A frequency accumulation (FA) method is proposed to suppress mixed products of the heartbeat and respiration signals and spurious respiration signal harmonics. The respiration frequency is estimated using the phase variations in the received signal, and a discrete short-time Fourier transform (DSFT) is used to estimate the range. The performance of the proposed system is evaluated along with that of several well-known techniques in the literature.
Highlights
Previous researches on human vital sign detection have focused on suppressing stationary and/or nonstationary clutters, estimating the respiration frequency and heart rate, the analysis of signal characteristics, and other related problems21–42
The fast Fourier transform (FFT) method provides the worst performance as the frequency estimate from Fig. 24(d) is 0.12 Hz
All these results indicate that the presented algorithm has the smallest deviation and significantly outperforms the other algorithms
Summary
Previous researches on human vital sign detection have focused on suppressing stationary and/or nonstationary clutters, estimating the respiration frequency and heart rate, the analysis of signal characteristics, and other related problems. In28, the arctangent demodulation (AD) technique was employed in a UWB pulse radar system to accurately extract vital sign signals over long distances and in and through-wall conditions. This technique is complex and decreases the computational efficiency. Most detection techniques are not effective over long distances and in through-wall conditions To solve these problems, an algorithm based on UWB radar is developed here to calculate accurately vital sign signals in challenging environments. Vital sign signals may be obtained due to the time delay changes of a transmitted
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