scholarly journals Searching for Survivors through Random Human-Body Movement Outdoors by Continuous-Wave Radar Array

PLoS ONE ◽  
2016 ◽  
Vol 11 (4) ◽  
pp. e0152201 ◽  
Author(s):  
Chuantao Li ◽  
Fuming Chen ◽  
Fugui Qi ◽  
Miao Liu ◽  
Zhao Li ◽  
...  
Keyword(s):  
Human Body ◽  
Continuous Wave ◽  
Body Movement ◽  
Wave Radar

scholarly journals Remote Monitoring of Human Vital Signs Based on 77-GHz mm-Wave FMCW Radar

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2999 ◽  
Author(s):  
Yong Wang ◽  
Wen Wang ◽  
Mu Zhou ◽  
Aihu Ren ◽  
Zengshan Tian
Keyword(s):  
Millimeter Wave ◽  
Human Body ◽  
Continuous Wave ◽  
Intermediate Frequency ◽  
Detection Methods ◽  
Discrete Wavelet ◽  
Phase Information ◽  
Millimeter Wave Radar ◽  
Wave Radar ◽  
Radar Sensing

In recent years, non-contact radar detection technology has been able to achieve long-term and long-range detection for the breathing and heartbeat signals. Compared with contact-based detection methods, it brings a more comfortable and a faster experience to the human body, and it has gradually received attention in the field of radar sensing. Therefore, this paper extends the application of millimeter-wave radar to the field of health care. The millimeter-wave radar first transmits the frequency-modulated continuous wave (FMCW) and collects the echo signals of the human body. Then, the phase information of the intermediate frequency (IF) signals including the breathing and heartbeat signals are extracted, and the Direct Current (DC) offset of the phase information is corrected using the circle center dynamic tracking algorithm. The extended differential and cross-multiply (DACM) is further applied for phase unwrapping. We propose two algorithms, namely the compressive sensing based on orthogonal matching pursuit (CS-OMP) algorithm and rigrsure adaptive soft threshold noise reduction based on discrete wavelet transform (RA-DWT) algorithm, to separate and reconstruct the breathing and heartbeat signals. Then, a frequency-domain fast Fourier transform and a time-domain autocorrelation estimation algorithm are proposed to calculate the respiratory and heartbeat rates. The proposed algorithms are compared with the contact-based detection ones. The results demonstrate that the proposed algorithms effectively suppress the noise and harmonic interference, and the accuracies of the proposed algorithms for both respiratory rate and heartbeat rate reach about 93%.

scholarly journals Vital Signal Detection Using Multi-Radar for Reductions in Body Movement Effects

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7398
Author(s):  
Ah-Jung Jang ◽  
In-Seong Lee ◽  
Jong-Ryul Yang
Keyword(s):  
Signal Detection ◽  
Continuous Wave ◽  
Signal To Noise Ratio ◽  
Body Movement ◽  
Phase Variation ◽  
Maximum Velocity ◽  
The Body ◽  
Wave Radar ◽  
The Difference ◽  
Correlated Signals

Vital signal detection using multiple radars is proposed to reduce the signal degradation from a subject’s body movement. The phase variation in the transceiving signals of continuous-wave radar due to respiration and heartbeat is generated by the body surface movement of the organs monitored in the line-of-sight (LOS) of the radar. The body movement signals obtained by two adjacent radars can be assumed to be the same over a certain distance. However, the vital signals are different in each radar, and each radar has a different LOS because of the asymmetric movement of lungs and heart. The proposed method uses two adjacent radars with different LOS to obtain correlated signals that reinforce the difference in the asymmetrical movement of the organs. The correlated signals can improve the signal-to-noise ratio in vital signal detection because of a reduction in the body movement effect. Two radars at different frequencies in the 5.8 GHz band are implemented to reduce direct signal coupling. Measurement results using the radars arranged at angles of 30°, 45°, and 60° showed that the proposed method can detect the vital signals with a mean accuracy of 97.8% for the subject moving at a maximum velocity of 53.4 mm/s.

scholarly journals Analysis of the Snow Water Equivalent at the AEMet-Formigal Field Laboratory (Spanish Pyrenees) During the 2019/2020 Winter Season Using a Stepped-Frequency Continuous Wave Radar (SFCW)

2021 ◽  
Vol 13 (4) ◽  
pp. 616
Author(s):  
Rafael Alonso ◽  
José María García del Pozo ◽  
Samuel T. Buisán ◽  
José Adolfo Álvarez
Keyword(s):  
Software Defined Radio ◽  
Continuous Wave ◽  
Snow Water Equivalent ◽  
Cosmic Ray ◽  
Relative Dielectric Permittivity ◽  
Near Surface ◽  
Wave Radar ◽  
Spanish Pyrenees ◽  
Snow Water ◽  
Stepped Frequency

Snow makes a great contribution to the hydrological cycle in cold regions. The parameter to characterize available the water from the snow cover is the well-known snow water equivalent (SWE). This paper presents a near-surface-based radar for determining the SWE from the measured complex spectral reflectance of the snowpack. The method is based in a stepped-frequency continuous wave radar (SFCW), implemented in a coherent software defined radio (SDR), in the range from 150 MHz to 6 GHz. An electromagnetic model to solve the electromagnetic reflectance of a snowpack, including the frequency and wetness dependence of the complex relative dielectric permittivity of snow layers, is shown. Using the previous model, an approximated method to calculate the SWE is proposed. The results are presented and compared with those provided by a cosmic-ray neutron SWE gauge over the 2019–2020 winter in the experimental AEMet Formigal-Sarrios test site. This experimental field is located in the Spanish Pyrenees at an elevation of 1800 m a.s.l. The results suggest the viability of the approximate method. Finally, the feasibility of an auxiliary snow height measurement sensor based on a 120 GHz frequency modulated continuous wave (FMCW) radar sensor, is shown.

scholarly journals Feasibility of Using Floor Vibration to Detect Human Falls

2020 ◽  
Vol 18 (1) ◽  
pp. 200
Author(s):  
Yu Shao ◽  
Xinyue Wang ◽  
Wenjie Song ◽  
Sobia Ilyas ◽  
Haibo Guo ◽  
...  
Keyword(s):  
Machine Learning ◽  
Human Body ◽  
Nearest Neighbor ◽  
Body Movement ◽  
Modern Society ◽  
Recognition System ◽  
Machine Learning Algorithms ◽  
K Nearest Neighbor ◽  
Study Results ◽  
Floor Vibration

With the increasing aging population in modern society, falls as well as fall-induced injuries in elderly people become one of the major public health problems. This study proposes a classification framework that uses floor vibrations to detect fall events as well as distinguish different fall postures. A scaled 3D-printed model with twelve fully adjustable joints that can simulate human body movement was built to generate human fall data. The mass proportion of a human body takes was carefully studied and was reflected in the model. Object drops, human falling tests were carried out and the vibration signature generated in the floor was recorded for analyses. Machine learning algorithms including K-means algorithm and K nearest neighbor algorithm were introduced in the classification process. Three classifiers (human walking versus human fall, human fall versus object drop, human falls from different postures) were developed in this study. Results showed that the three proposed classifiers can achieve the accuracy of 100, 85, and 91%. This paper developed a framework of using floor vibration to build the pattern recognition system in detecting human falls based on a machine learning approach.

scholarly journals A Local Oscillator Phase Compensation Technique for Ultra-Wideband Stepped-Frequency Continuous Wave Radar Based on a Low-Cost Software-Defined Radio

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 780
Author(s):  
Kazunori Takahashi ◽  
Takashi Miwa
Keyword(s):  
Software Defined Radio ◽  
Initial Phase ◽  
Continuous Wave ◽  
Low Cost ◽  
Local Oscillator ◽  
The Other ◽  
Ultra Wideband ◽  
Single Frequency ◽  
Wave Radar ◽  
Stepped Frequency

The paper discusses a way to configure a stepped-frequency continuous wave (SFCW) radar using a low-cost software-defined radio (SDR). The most of high-end SDRs offer multiple transmitter (TX) and receiver (RX) channels, one of which can be used as the reference channel for compensating the initial phases of TX and RX local oscillator (LO) signals. It is same as how commercial vector network analyzers (VNAs) compensate for the LO initial phase. These SDRs can thus acquire phase-coherent in-phase and quadrature (I/Q) data without additional components and an SFCW radar can be easily configured. On the other hand, low-cost SDRs typically have only one transmitter and receiver. Therefore, the LO initial phase has to be compensated and the phases of the received I/Q signals have to be retrieved, preferably without employing an additional receiver and components to retain the system low-cost and simple. The present paper illustrates that the difference between the phases of TX and RX LO signals varies when the LO frequency is changed because of the timing of the commencement of the mixing. The paper then proposes a technique to compensate for the LO initial phases using the internal RF loopback of the transceiver chip and to reconstruct a pulse, which requires two streaming: one for the device under test (DUT) channel and the other for the internal RF loopback channel. The effect of the LO initial phase and the proposed method for the compensation are demonstrated by experiments at a single frequency and sweeping frequency, respectively. The results show that the proposed method can compensate for the LO initial phases and ultra-wideband (UWB) pulses can be reconstructed correctly from the data sampled by a low-cost SDR.

Multi-target Vital Signs Detection Using SIMO Continuous-wave Radar with DBF Technique

2020 ◽  
Author(s):  
Junjun Xiong ◽  
Hongqiang Zhang ◽  
Hong Hong ◽  
Heng Zhao ◽  
Xiaohua Zhu ◽  
...  
Keyword(s):  
Continuous Wave ◽  
Vital Signs ◽  
Wave Radar

scholarly journals A Doppler Range Compensation for Step-Frequency Continuous-Wave Radar for Detecting Small UAV

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1331
Author(s):  
Massimiliano Pieraccini ◽  
Lapo Miccinesi ◽  
Neda Rojhani
Keyword(s):  
Short Range ◽  
Continuous Wave ◽  
Range Shift ◽  
Specific Method ◽  
Step Frequency ◽  
Wave Radar ◽  
Small Uav ◽  
The Doppler Effect ◽  
Set Up ◽  
Free Falling

Step-frequency continuous-wave (SFCW) modulation can have a role in the detection of small unmanned aerial vehicles (UAV) at short range (less than 1–2 km). In this paper, the theory of SFCW range detection is reviewed, and a specific method for correcting the possible range shift due to the Doppler effect is devised. The proposed method was tested in a controlled experimental set-up, where a free-falling target (i.e., a corner reflector) was correctly detected by an SFCW radar. This method was finally applied in field for short-range detection of a small UAV.

Sign in / Sign up

Export Citation Format

Share Document