scholarly journals A Novel Method for Breath Detection via Stepped-Frequency Continuous Wave Ultra-Wideband (SFCW UWB) Radars Based on Operational Bandwidth Segmentation

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3873 ◽  
Author(s):  
Hao Lv ◽  
Teng Jiao ◽  
Yang Zhang ◽  
Fulai Liang ◽  
Fugui Qi ◽  
...  
Keyword(s):  
Continuous Wave ◽  
Doppler Radar ◽  
Ultra Wideband ◽  
Time Dimension ◽  
Processing Scheme ◽  
Practical Applications ◽  
Uwb Radar ◽  
Operational Frequency ◽  
Stepped Frequency ◽  
Breath Detection

Human being detection via ultra-wideband (UWB) radars has shown great prospects in many areas, such as biomedicine, military operation, public security, emergency rescue, and so on. When a person stays stationary, the main feature that separates him/her from surroundings is the movement of chest wall due to breath. There have been many algorithms developed for breath detection while using UWB radars. However, those algorithms were almost based on a basic scheme that focused on processing in the time dimension of UWB data. They did not utilize the benefits from the wide operational bandwidth of UWB radars to show potential superiority over those narrowband systems such as a continuous wave (CW) Doppler radar. In this paper, a breath detection method was proposed based on operational bandwidth segmentation. A basic theoretical model was firstly introduced, indicating that characteristics of breath signals contained in UWB echoes were consistent among the operational frequencies, while those of clutters were not. So, the method divided a set of UWB echo data into a number of subsets, each of which corresponded to a sub-band within the operational bandwidth of the UWB radar. Thus information about the operational frequency is provided for subsequent processing. With the aid of the information, a breath enhancement algorithm was developed mainly by averaging the segmented UWB data along the operational frequency. The algorithm’s performance was verified by data measured by a stepped-frequency CW (SFCW) UWB radar. The experimental results showed that the algorithm performed better than that without the segmentation. They also showed its feasibility for fast detection of breath based on a short duration of data. Moreover, the method’s potential for target identification and impulse-radio (IR) UWB radar was investigated. In summary, the method provides a new processing scheme for UWB radars when they are used for breath detection. With this scheme, the UWB radars have a benefit of greater flexibility in data processing over those narrowband radars, and thus will perform more effectively and efficiently in practical applications.

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.

scholarly journals Adaptive Separation of Respiratory and Heartbeat Signals among Multiple People Based on Empirical Wavelet Transform Using UWB Radar

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4913 ◽  
Author(s):  
Mi He ◽  
Yongjian Nian ◽  
Luping Xu ◽  
Lihong Qiao ◽  
Wenwu Wang
Keyword(s):  
Wavelet Transform ◽  
Continuous Wave ◽  
Body Movement ◽  
Vital Signs ◽  
Initial Boundary ◽  
Tight Frame ◽  
Ultra Wideband ◽  
Clinical Monitoring ◽  
Uwb Radar ◽  
Empirical Wavelet Transform

The non-contact monitoring of vital signs by radar has great prospects in clinical monitoring. However, the accuracy of separated respiratory and heartbeat signals has not satisfied the clinical limits of agreement. This paper presents a study for automated separation of respiratory and heartbeat signals based on empirical wavelet transform (EWT) for multiple people. The initial boundary of the EWT was set according to the limited prior information of vital signs. Using the initial boundary, empirical wavelets with a tight frame were constructed to adaptively separate the respiratory signal, the heartbeat signal and interference due to unconscious body movement. To verify the validity of the proposed method, the vital signs of three volunteers were simultaneously measured by a stepped-frequency continuous wave ultra-wideband (UWB) radar and contact physiological sensors. Compared with the vital signs from contact sensors, the proposed method can separate the respiratory and heartbeat signals among multiple people and obtain the precise rate that satisfies clinical monitoring requirements using a UWB radar. The detection errors of respiratory and heartbeat rates by the proposed method were within ±0.3 bpm and ±2 bpm, respectively, which are much smaller than those obtained by the bandpass filtering, empirical mode decomposition (EMD) and wavelet transform (WT) methods. The proposed method is unsupervised and does not require reference signals. Moreover, the proposed method can obtain accurate respiratory and heartbeat signal rates even when the persons unconsciously move their bodies.

scholarly journals Short-Range Vital Signs Sensing Based on EEMD and CWT Using IR-UWB Radar

2016 ◽  
Author(s):  
Xikun Hu ◽  
Tian Jin
Keyword(s):  
Doppler Radar ◽  
Signal To Noise Ratio ◽  
Vital Signs ◽  
Ensemble Empirical Mode Decomposition ◽  
The Body ◽  
Ultra Wideband ◽  
Detection Range ◽  
Wall Movement ◽  
Uwb Radar ◽  
Mode Decomposition

The radar sensor described realizes healthcare monitoring capable of detecting subject chest-wall movement caused by cardiopulmonary activities, and wirelessly estimating the respiration and heartbeat rates of the subject without attaching any devices to the body. Conventional single-tone Doppler radar can only capture Doppler signatures because of a lack of bandwidth information with noncontact sensors. In contrast, we take full advantage of impulse radio ultra-wideband (IR-UWB) radar to achieve low power consumption and convenient portability, with a flexible detection range and desirable accuracy. A noise reduction method based on improved ensemble empirical mode decomposition (EEMD) and a vital sign separation method based on the continuous-wavelet transform (CWT) are proposed jointly to improve the signal-to-noise ratio (SNR) in order to acquire accurate respiration and heartbeat rates. Experimental results illustrate that respiration and heartbeat signals can be extracted accurately under different conditions. This noncontact healthcare sensor system proves the commercial feasibility and considerable accessibility of using compact IR-UWB radar for emerging biomedical applications.

Monostatic continuous-wave radar integrating a tunable wideband leakage canceler for indoor tagless localization

2017 ◽  
Vol 9 (8) ◽  
pp. 1583-1590 ◽  
Author(s):  
Marco Mercuri ◽  
Paweł Barmuta ◽  
Ping Jack Soh ◽  
Paul Leroux ◽  
Dominique Schreurs
Keyword(s):  
Health Monitoring ◽  
Continuous Wave ◽  
Dynamic Range ◽  
Passive Microwave ◽  
Ultra Wideband ◽  
Strong Reduction ◽  
Wave Radar ◽  
Microwave Design ◽  
Stepped Frequency ◽  
Cw Radar

Continuous-wave (CW) radars have been recently investigated in healthcare aiming at contactless health monitoring. However, a major problem in monostatic CW architectures is represented by the unwanted leakage produced by poor isolation between transmitter and receiver, which can drastically decrease the receiver's sensitivity reducing therefore the radar dynamic range. Although this situation can be easily controlled in case of narrowband CW radar by an appropriate passive microwave design, it becomes much more complicated in case of stepped-frequency CW and frequency-modulated CW architectures that present an ultra-wideband nature. In this paper, a monostatic CW radar integrating a tunable wideband leakage canceler aiming at indoor tagless localization is presented and discussed. The use of the feedforward canceler allows a strong reduction of the unwanted leakage over the whole radar bandwidth. Experimental results demonstrate the feasibility of this approach, showing an outstanding improvement of the radar dynamic range.

scholarly journals Experimental Comparison of IR-UWB Radar and FMCW Radar for Vital Signs

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6695
Author(s):  
Dingyang Wang ◽  
Sungwon Yoo ◽  
Sung Ho Cho
Keyword(s):  
Continuous Wave ◽  
Vital Signs ◽  
Ultra Wideband ◽  
Experimental Comparison ◽  
Distance Information ◽  
Mimo Antenna ◽  
Fmcw Radar ◽  
Uwb Radar ◽  
Sign Detection ◽  
Detection Capabilities

In this paper, we compare the performances of impulse radio ultra-wideband (IR-UWB) and frequency modulation continuous wave (FMCW) radars in measuring noncontact vital signs such as respiration rate and heart rate. These two type radars have been widely used in various fields and have shown their applicability to extract vital signs in noncontact ways. IR-UWB radar can extract vital signs using distance information. On the other hand, FMCW radar requires phase information to estimate vital signs, and the result can be enhanced with Multi-input Multi-output (MIMO) antenna topologies. By using commercial radar chipsets, the operation of radars under different conditions and frequency bands will also affect the performance of vital sign detection capabilities. We compared the accuracy and signal-to-noise (SNR) ratios of IR-UWB and FMCW radars in various scenarios, such as distance, orientation, carotid pulse, harmonics, and obstacle penetration. In general, the IR-UWB radars offer a slightly better accuracy and higher SNR in comparison to FMCW radar. However, each radar system has its own unique advantages, with IR-UWB exhibiting fewer harmonics and a higher SNR, while FMCW can combine the results from each channel.

A Study of Clustering for the Enhancement of Image Resolution in Dynamic Photon Emission

2019 ◽  
Author(s):  
S. Chef ◽  
C. T. Chua ◽  
C. L. Gan
Keyword(s):  
Signal To Noise Ratio ◽  
Photon Emission ◽  
Optical Signal ◽  
Image Resolution ◽  
Time Dimension ◽  
Processing Scheme ◽  
3D Space ◽  
Initial Acquisition ◽  
Resolution Limits ◽  
Emission Microscopy

Abstract Limited spatial resolution and low signal to noise ratio are some of the main challenges in optical signal observation, especially for photon emission microscopy. As dynamic emission signals are generated in a 3D space, the use of the time dimension in addition to space enables a better localization of switching events. It can actually be used to infer information with a precision above the resolution limits of the acquired signals. Taking advantage of this property, we report on a post-acquisition processing scheme to generate emission images with a better image resolution than the initial acquisition.

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 High Accuracy Heartbeat Detection from CW-Doppler Radar Using Singular Value Decomposition and Matched Filter

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3588
Author(s):  
Yuki Iwata ◽  
Han Trong Thanh ◽  
Guanghao Sun ◽  
Koichiro Ishibashi
Keyword(s):  
Heart Rate ◽  
Singular Value Decomposition ◽  
Continuous Wave ◽  
Doppler Radar ◽  
Matched Filter ◽  
Singular Value ◽  
Home Healthcare ◽  
Body Motion ◽  
Sitting Posture ◽  
Value Decomposition

Heart rate measurement using a continuous wave Doppler radar sensor (CW-DRS) has been applied to cases where non-contact detection is required, such as the monitoring of vital signs in home healthcare. However, as a CW-DRS measures the speed of movement of the chest surface, which comprises cardiac and respiratory signals by body motion, extracting cardiac information from the superimposed signal is difficult. Therefore, it is challenging to extract cardiac information from superimposed signals. Herein, we propose a novel method based on a matched filter to solve this problem. The method comprises two processes: adaptive generation of a template via singular value decomposition of a trajectory matrix formed from the measurement signals, and reconstruction by convolution of the generated template and measurement signals. The method is validated using a dataset obtained in two different experiments, i.e., experiments involving supine and seated subject postures. Absolute errors in heart rate and standard deviation of heartbeat interval with references were calculated as 1.93±1.76bpm and 57.0±28.1s for the lying posture, and 9.72±7.86bpm and 81.3±24.3s for the sitting posture.

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