An experimental study: Detecting the respiration rates of multiple stationary human targets by stepped frequency continuous wave radar

Acar, Yunus Emre; Sarıtaş, İsmail; Yaldiz, Ercan

doi:10.1016/j.measurement.2020.108268

Cited by 15 publications

(15 citation statements)

References 42 publications

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“…more intuitive display, we duplicate it to generate a matrix of size 800 × 600, keepi same size as the range-slow-time matrix. The red dots represent the result of clust and the target range output by the method is 3.62 m. Furthermore, the detection method based on a 1D range profile in [34], the det method based on a 2D range-frequency matrix in [35], and the method in [36] wer formed for comparison with the proposed method. Figure 7 shows the result method in [34].…”

Section: Experiments With a Single Targetmentioning

confidence: 99%

“…The detectio at 3.63 m is regarded as the human target signal. The peak at the range of 0.79 m is to estimate the clutter energy, and its correlation coefficient is 0.17, which is lowe Furthermore, the detection method based on a 1D range profile in [34], the detectio method based on a 2D range-frequency matrix in [35], and the method in [36] were pe formed for comparison with the proposed method. Figure 7 shows the result of th method in [34].…”

Section: Experiments With a Single Targetmentioning

confidence: 99%

“…The threshold r T in [35] is set to 1.5. It can be seen that the method in [35] also correctly extracts the human target, and the output target range is 3.59 m. Figure 9 shows the processed result by the method in [36]. A range-dependent threshold signal is generated, and hard thresholding is applied to the range profile.…”

Section: Experiments With a Single Targetmentioning

confidence: 99%

“…As can be seen from Figure 9, the threshold signal with  of 10 ca extract the target at 3.63 m. In the single-target detection experiment, all four method correctly extract the target range. Figure 9 shows the processed result by the method in [36]. A range-dependent threshold signal is generated, and hard thresholding is applied to the range profile.…”

Section: Experiments With a Single Targetmentioning

confidence: 99%

“…They design the constant false alarm ratio (CFAR) energy windows based on the characteristic of life sign. Acar et al [36] proposed a range-dependent thresholding which decreases exponentially and hard thresholding is applied to the range profile. However, these three methods are energy-based automatic detection methods, and there will be missed alarms in the case of multiple human targets.…”

Section: Introductionmentioning

confidence: 99%

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Multiple Stationary Human Targets Detection in Through-Wall UWB Radar Based on Convolutional Neural Network

et al. 2022

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Ultra-wideband (UWB) impulse radar is widely used for through-wall human detection due to its high-range resolution and high penetration capability. UWB impulse radar can detect human targets in non-line-of-sight (NLOS) conditions, mainly based on the chest motion caused by human respiration. The automatic detection and extraction of multiple stationary human targets is still a challenge. Missed alarms often exist if the detection method is based on the energy of the human target. This is mainly because factors such as the range of the target, the intensity of the respiratory movement, and the shadow effect will make a difference between the energy scattered by targets. Weak targets are easily masked by strong targets and thus cannot be detected. Therefore, in this paper, a multiple stationary human targets detection method based on convolutional neural network (CNN) in through-wall UWB impulse radar is proposed. After performing the signal-to-clutter-and-noise ratio (SCNR) enhancement method on the raw radar data, the range-slow-time matrix is fed into a six-layer CNN. Benefiting from the powerful feature extraction capability of CNN, the target point of interest (TPOI) can be extracted from the data matrix. The clustering algorithm is used to simplify the TPOIs to achieve accurate detection of multiple targets behind the wall. The effectiveness of the proposed method is verified by the experimental data.

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