Ultra-wide band impulse radar for life detection using wavelet packet decomposition

Liang, Xiaolin; Zhang, Hao; Lyu, Tingting; Xu, Lingwei; Cao, Conghui; Gulliver, T. Aaron

doi:10.1016/j.phycom.2018.04.004

Cited by 20 publications

(15 citation statements)

References 43 publications

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“…The performance of the proposed, FFT, constant false alarm ratio (CFAR) 34 , and MHOC 37 methods as well as the advanced method (AM) 36 , the FA method with different times, and the CSD 42 and logarithm CSD (LCSD) techniques are evaluated in the following sections using the experimental data.…”

Section: Performance Resultsmentioning

confidence: 99%

Ultra-Wideband Impulse Radar Through-Wall Detection of Vital Signs

Liang¹,

Deng²,

Zhang

et al. 2018

Sci Rep

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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.

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Section: Performance Resultsmentioning

confidence: 99%

Ultra-Wideband Impulse Radar Through-Wall Detection of Vital Signs

Liang¹,

Deng²,

Zhang

et al. 2018

Sci Rep

Self Cite

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“…where τ and µ r are given by (28) and (29), respectively. The SNR decreases with distance due to signal attenuation [37].…”

Section: Detection Performancementioning

confidence: 99%

“…To avoid the codomain restriction in arctangent demodulation (AD), an extended differentiate and cross-multiply (DACM) method was proposed in [21]. Existing vital sign detection techniques are not suitable for trapped victims because they consider only some of the issues, such as removing clutter, determining respiration characteristics, and heart rate estimation [23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41]. An algorithm for vital sign detection based on radar data was developed in [16].…”

Section: Introductionmentioning

confidence: 99%

“…The respiration period was estimated in [28] for an additive white Gaussian noise (AWGN) environment [28]. Respiration detection in low signal to noise and clutter ratio (SNCR) conditions was considered in [29] using singular value decomposition (SVD). The method proposed in [34] to detect signs of life is only effective over short distances and in high signal to noise ratio (SNR) environments.…”

Section: Introductionmentioning

confidence: 99%

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Clutter Elimination and Harmonic Suppression of Non-Stationary Life Signs for Long-Range and Through-Wall Human Subject Detection Using Spectral Kurtosis Analysis (SKA)-Based Windowed Fourier Transform (WFT) Method

Yang

Qin

Liang³

et al. 2019

Applied Sciences

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Life sign detection is important in many applications, such as locating disaster victims. This can be difficult in low signal to noise ratio (SNR) and through-wall conditions. This paper considers life sign detection using an impulse ultra-wideband (UWB) bio-radar with an improved sensing algorithm for clutter elimination, harmonic suppression and random-noise de-noising. To improve detection performance, two filters are used to improve SNR of these life signs. The automatic gain method is performed in fast time to improve the respiration signals. The spectral kurtosis analysis (SKA)-based windowed Fourier transform (WFT) method and an accumulator in the frequency domain are used to provide two distance estimates between the radar and human subject. Further, the accumulator can also provide the frequency estimate of the respiration signals. These estimates are used to determine if a human is present in the detection environment. Results are presented which show that the range and respiration frequency can be estimated accurately in low signal to noise and clutter ratio (SNCR) environments. In addition, the performance is better than with other techniques given in the literature.

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“…An effective application of automatic gain control method is to enhance the amplitudes of the weak signals in radar systems [33]. Via adjusting the gain values based on the calculated power of the signals in a window w, the key is to compare the gain values and g max as…”

Section: Automatic Gain Controlmentioning

confidence: 99%

An Improved RF Detection Algorithm Using EMD-based WT

2019

KSII TIIS

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More and more problems for public security have occurred due to the limited solutions for drone detection especially for micro-drone in long range conditions. This paper aims at dealing with drones detection using a radar system. The radio frequency (RF) signals emitted by a controller can be acquired using the radar, which are usually too weak to extract. To detect the drone successfully, the static clutters and linear trend terms are suppressed based on the background estimation algorithm and linear trend suppression. The principal component analysis technique is used to classify the noises and effective RF signals. The automatic gain control technique is used to enhance the signal to noise ratios (SNR) of RF signals. Meanwhile, the empirical mode decomposition (EMD) based wavelet transform (WT) is developed to decrease the influences of the Gaussian white noises. Then, both the azimuth information between the drone and radar and the bandwidth of the RF signals are acquired based on the statistical analysis algorithm developed in this paper. Meanwhile, the proposed accumulation algorithm can also provide the bandwidth estimation, which can be used to make a decision accurately whether there are drones or not in the detection environments based on the probability theory. The detection performance is validated with several experiments conducted outdoors with strong interferences.

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Ultra-wide band impulse radar for life detection using wavelet packet decomposition

Cited by 20 publications

References 43 publications

Ultra-Wideband Impulse Radar Through-Wall Detection of Vital Signs

Ultra-Wideband Impulse Radar Through-Wall Detection of Vital Signs

Clutter Elimination and Harmonic Suppression of Non-Stationary Life Signs for Long-Range and Through-Wall Human Subject Detection Using Spectral Kurtosis Analysis (SKA)-Based Windowed Fourier Transform (WFT) Method

An Improved RF Detection Algorithm Using EMD-based WT

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