Continuous Wave Doppler Radar Research Articles

Uncertainty in remote sensing of streams using noncontact radars

Accounting for freshwater resources and monitoring floods are vital functions for societies throughout the world. Remote-sensing methods offer great prospects to expand stream monitoring in developing countries and to smaller, headwater streams that are largely ungauged worldwide. This study evaluates the potential to estimate discharge using eight radar units that have been installed over streams in diverse hydrologic and hydraulic settings across the United States. The research highlights error characteristics associated with the measurements of stage using pulsed wave radars, mean channel velocity from continuous wave Doppler radars, and their combined use to estimate discharge at sites that were collocated with conventional streamgauges. Potential stage biases caused by the thermal expansion and contraction of supporting structures due to diurnal temperature changes were examined. A dry concrete, flume showed the temperature-dependent stage variations were no more than 2 cm. Surface velocity retrievals needed to be adjusted to represent the mean channel velocity when estimating discharge. Different approaches were evaluated and application of two different, depth-dependent adjustment factors was found to yield the most accurate estimates. This study found that it is possible to get accurate discharge estimates from noncontact radar measurements, providing cost-effective solutions for remote sensing of ungauged streams. Lastly, radar measurements of the raw variables (i.e., stage and surface velocity) can be used in an early alerting context to detect flash floods in ungauged streams.

Through-Wall Multi-Subject Localization and Vital Signs Monitoring Using UWB MIMO Imaging Radar

Radar-based non-contact vital signs monitoring has great value in through-wall detection applications. This paper presents the theoretical and experimental study of through-wall respiration and heartbeat pattern extraction from multiple subjects. To detect the vital signs of multiple subjects, we employ a low-frequency ultra-wideband (UWB) multiple-input multiple-output (MIMO) imaging radar and derive the relationship between radar images and vibrations caused by human cardiopulmonary movements. The derivation indicates that MIMO radar imaging with the stepped-frequency continuous-wave (SFCW) improves the signal-to-noise ratio (SNR) critically by the factor of radar channel number times frequency number compared with continuous-wave (CW) Doppler radars. We also apply the three-dimensional (3-D) higher-order cumulant (HOC) to locate multiple subjects and extract the phase sequence of the radar images as the vital signs signal. To monitor the cardiopulmonary activities, we further exploit the VMD algorithm with a proposed grouping criterion to adaptively separate the respiration and heartbeat patterns. A series of experiments have validated the localization and detection of multiple subjects behind a wall. The VMD algorithm is suitable for separating the weaker heartbeat pattern from the stronger respiration pattern by the grouping criterion. Moreover, the continuous monitoring of heart rate (HR) by the MIMO radar in real scenarios shows a strong consistency with the reference electrocardiogram (ECG).

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

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 and for the lying posture, and and for the sitting posture.

Microstrip patch and Sierpinski fractal antennas: simulations and experimental characterization for vital signs detection with Doppler radar technique

Objectives: To fabricate planar models of antennas with resonance frequencies in the ultrahigh frequency band that allow short-range detection of respiration and heartbeat by a simple continuous wave Doppler radar system. Methods: Models of antennas were created in CST Studio software and the main parameters were computed. Then, antennas were fabricated at a PCB prototyping machine and were experimentally characterized in an anechoic chamber. Total efficiency and radiation patterns indicated the best working frequencies of 2.12 GHz and 8.82 GHz respectively, to test the human vital signs detection with a continuous-wave Doppler radar technique in direct visibility conditions. Findings: The patch antenna at 2.12 GHz had a maximum gain of 3.15 dBi and total efficiency of 43% while the Sierpinski antenna at 8.82 GHz had a maximum gain of 5.5 dBi and total efficiency of 65%. At incident power densities on the human subject’s chest of 4.5 x 10-4 mW/m2 and of 2.6 x 10-2 mW/m2 respectively, the Doppler radar system based on these antennas offered precise responses. Practically, it was possible to extract both the heartbeat rate and the respiration rate, by simply applying the classical FFT algorithm on a time-series phase data of the transmission coefficient recorded during 30 seconds, when the set-up was composed of just the antennas and a vector network analyzer. Novelty: Increased detection accuracy was obtained due to careful characterization of the antennas parameters with no need of special processing algorithms. Keywords: Sierpinski Antenna; Patch Antenna; CW Doppler Radar; Respiration Rate; Heartbeat Rate

Elderly Fall Detection With Vital Signs Monitoring Using CW Doppler Radar

Falling is the main cause of disability and fatality of elderly. In this work we used a 24 GHz continuous-wave Doppler radar to develop a low price and a highly accurate fall detection system aiming at observing indoor human activities and detecting fall accidents, thus limiting the consequences of undiscovered falls. A radar sensor was selected due to its capability of tracking human motions, passing through obstacles, and not being affected by light conditions. The sampled signals from the sensor were subjected to different feature engineering and machine learning techniques in order to determine the most characteristic features. Consequently, we were able to extract nontraditional radar features. Moreover, to improve the systems responsiveness and to lessen the hardware constraints, we added an additional pre-processing step to detect major physical activities with O(N) complexity. As part of fall detection, we also implemented vital signs monitoring to reduce false positives and to alert concerned authorities if necessary. Experimental results show that our proposed system has 90% recall rate for fall detection and 97.7% and 95.3% accuracy rates for respiration and heartbeat detection respectively.

Contact and Remote Breathing Rate Monitoring Techniques: A Review.

Breathing rate monitoring is a must for hospitalized patients with the current coronavirus disease 2019 (COVID-19). We review in this paper recent implementations of breathing monitoring techniques, where both contact and remote approaches are presented. It is known that with non-contact monitoring, the patient is not tied to an instrument, which improves patients’ comfort and enhances the accuracy of extracted breathing activity, since the distress generated by a contact device is avoided. Remote breathing monitoring allows screening people infected with COVID-19 by detecting abnormal respiratory patterns. However, non-contact methods show some disadvantages such as the higher set-up complexity compared to contact ones. On the other hand, many reported contact methods are mainly implemented using discrete components. While, numerous integrated solutions have been reported for non-contact techniques, such as continuous wave (CW) Doppler radar and ultrawideband (UWB) pulsed radar. These radar chips are discussed and their measured performances are summarized and compared.

Janus: A Combined Radar and Vibration Sensor for Beehive Monitoring

A novel beehive monitoring sensor with two faces is described. This sensor is attached to the outside of a hive, near the hive entrance. The outward-looking sensor is a 24-GHz continuous-wave Doppler radar for monitoring bee flying activity. The inward-looking sensor is a piezoelectric transducer. Unlike a conventional microphone that would pick up the sounds bees make, the piezoelectric transducer picks up the incidental vibrations transmitted by bee activity to the hive structure. The root-mean-square powers in concurrent radar and vibration measurements are shown to be highly correlated during honeybee swarming and robbing events. Principal component analysis was applied to radar, vibration, and environmental measurements to further reduce false alarms.

Simulation research on vital sign detection radar system

In order to solve the problem of the null detection point in the vital signs detection based on continuous wave(CW) Doppler radar, a novel dual-band hybrid down-conversion radar transceiver system is proposed. The proposed radar system operating frequency is 2.05 GHz and 1.64 GHz. Correlation between signals can improve the overall performance of the system. At λ/4 distance, the single-band single-channel detection has the problem of null detection point, and the proposed dual-band double-channel detection can solve the null detection point. On the other hand, at the non-λ/4 distance, the results of the dual-band detection double-channel can be mutually verified, ensuring the detection accuracy of the vital sign detection system. The simulation results prove the feasibility of the radar system. Regardless of whether the detected distance is at the λ/4 distance, the proposed vital sign detection system can always obtain the vital sign.

Fabry–Perot Beam Scanning Antenna for Remote Vital Sign Detection at 60 GHz

A beam scanning Fabry-Perot leaky-wave antenna (LWA) is designed at 60 GHz-band for single tone continuous-wave Doppler radar (DR)-based remote vital sign monitoring (RVSM) in a dynamic environment. A brief analysis is presented on antenna requirements for the DR in a typical dynamic scenario where a continuous RVSM is desired of a patient during sleep. The antenna is designed based on the drawn requirements with sufficiently high gain (>18 dBi) and wide beam scanning (12°) over the operating frequency band (62-65 GHz) for accurate RVSM up to 3 m distance. The patient under continuous health monitoring has a flexibility to change his/her position within 1 m angular distance from the fixed sensor position. Detailed RVSM measurements have been carried out with the proposed antenna system at 2 m and 3 m distances from the subject to verify the designed antenna's suitability for dynamic RVSM application. It has been shown that both the breathing rate (BR) and heartbeat rate (HR) can be successfully detected within 20° of the angular range by tuning the operating frequency from 62 to 65 GHz.

Дослідження поширення радіохвиль сантиметрового діапазону над морем із використанням високопотенційної доплерівської РЛС

Subject and Purpose. The paper is devoted to the microwave propagation over the sea in the nearshore region. Emphasis is on microwave attenuation measurements in the semi-shade and deep-shade areas with a view to study conditions of the microwave propagation on a beyond-the-horizon path in the nearshore area using a radar method. Methods and Methodology. A radar technique, developed and tested, provides measuring a microwave attenuation coefficient along a 60 km long beyond-the-horizon path in the tropospheric surface layer. High-grade radar and Doppler radar beacons (racons) are employed. Of interest are experimentally obtained temporal dependences of signals from racons situated at different heights and, also, spatial field distribution curves from a steadily moving racon running a height 1 to 27 m for 25 minutes. Results. A prototype of high-grade X-band coherent continuous-wave (Doppler) radar has been designed and fabricated. A radar technique has been developed and tested for the analysis of microwave beyond-the-horizon propagation conditions in the shadow region, which involves continuous-wave (Doppler) radar and Doppler racons with a radar cross section (RCS) of about 60 m2. Conclusions. The technique proposed enables reliable tracking of racon responses up to a double radiohorizon range on over-sea paths. This technique can be used for radar calibrations when dealing with various location problems in the nearshore area, including detection and tracking small-size and low-flying targets and their radar identification.

Comparative study of Kalman filter-based target motion analysis by incorporating Doppler frequency measurements

Abstract Target motion analysis is a key requirement of autonomous and self-driving machines like drones and robots. However, with strict weight limits, the aerospace industry is always on the hunt for simpler and lighter sensing solutions. Continuous-wave Doppler radars are the simplest radars that can easily obtain a target’s relative velocity using the Doppler shift in the received wave. However, these radars cannot provide the target’s range. In this work, we address the problem of obtaining target’s range and velocity by incorporating Doppler frequency measurements from a simple continuous wave Doppler radar. To this end, we find out the movement patterns and maneuvers that an observer can make to converge to the target’s location. After presenting the observability requirements, we design and compare various non-linear Kalman filter-based target trackers. We experimented with different simulation scenarios to compare the tracking results with bearings-only, frequency-only, and bearings-frequency measurement sets. In our analysis, Unscented Kalman Filter with bearings-frequency measurements performed best. Experiments show that an observer can locate the target accurately within 10 cm by incorporating Doppler frequency measurements. Moreover, it also reduced the convergence time to a fraction of a second.

Multiphase Continuous-Wave Doppler Radar With Multiarc Circle Fitting Algorithm for Small Periodic Displacement Measurement

A multiphase continuous-wave (MPCW) Doppler radar with a multiarc circle fitting (MACF) algorithm is proposed for improving the accuracy of small periodic displacement measurements. In the proposed radar, local oscillator (LO) signals with different phases are incident to multiple I/Q mixers, to simultaneously generate multiarcs for small periodic motions. The multiarcs obtained from the synchronized data are used in the circle fitting method to provide dc offset compensation, for accurate phase demodulation. The proposed MACF algorithm, based on the Levenberg–Marquardt method, can more precisely compensate for the dc offset by combining multiarcs generated from the proposed radar. A 5.8-GHz MPCW Doppler radar module with four-phased LO signals is implemented as a demonstration. The small periodic displacement of a metal plate on a single-axis linear stage is measured using the proposed radar module and algorithm. Compared with conventional CW Doppler radar using a single arc, measurement results using the proposed radar show that the root-mean-square error (RMSE) can be effectively decreased in the periodic motion from 1 to 2 mm, at distances from 30 to 60 cm. The RMSE is reduced by more than 33% for a peak-to-peak displacement of 1 mm at a distance of 60 cm.

Short time cardio-vascular pulses estimation for dengue fever screening via continuous-wave Doppler radar using empirical mode decomposition and continuous wavelet transform

Contactless measurement of cardio-vascular pulse acts an essential role in clinical medical sectors. Estimating cardio-vascular pulses based on continuous-wave (CW) Doppler radar in limited time while maintaining the accuracy is a challenging task. In this paper, we propose a signal processing method that combines empirical mode decomposition (EMD) and continuous wavelet transform (CWT) for a short time estimation of heart rate (HR) and inter-beat-interval from radar signals. We evaluate performance of the proposed method using 85 patients with dengue fever and 40 healthy subjects. Subsequently, the estimated contactless HR is compared to that of a commercial contact-type medical device. The result shows that the HR can be estimated within a period of 5 s with an accuracy of 96.2 ± 2.5%. The patients with dengue fever show an elevated HR and a decreased standard deviation of heartbeat interval (SDHI). Finally, linear discriminant analysis (LDA) is utilized with two parameters HR and SDHI to classify the dengue patients, achieving the sensitivity and specificity values of 86.3% and 86.9%, respectively.

FREQUENCY RESPONSE OF UWB SIGNAL IN A BEATING HEART

The measurement, monitoring of heartbeat and its rate are necessary to know the health of the heart of human beings. In addition, they are needed for extended applications like criminal investigation, law enforcement, defense and military usage, search, rescue operation, etc. The ultra-wideband (UWB) radars found growing interest in recent years as they are able to overcome the limitations of continuous-wave (CW) Doppler radars in detecting human heartbeat. Modeling and analysis of the UWB pulse propagation behavior through a human body is important before developing a practical UWB radar. Several researchers have estimated the reflected signals to study if their variations correlate with the heartbeat rate. However, the reflected signal strength carrying Doppler information received at the radar after a two-way propagation of the RF signal was found to be too weak for detection. This paper presents (i) a model for UWB wave propagation through a human thorax and (ii) estimation via simulation, of transmission coefficient at various frequencies in the UWB range 1–10[Formula: see text]GHz using CST Microwave Studio. The study clearly indicates that the variation of power transmission coefficient of UWB signal has a strong correlation to the instantaneous dimension of the heart in a cardiac cycle, a feature that can be exploited in detecting cardiac activity of human being using radar-based principles.

Real-time Measurement of Projectile Velocity in a Ballistic Fabric with a High-frequency Doppler Radar

Because of technical limitations, most experimental studies on the energy-absorbing properties of ballistic fabrics are limited to discrete evaluations based on impact and residual velocities. Consequently, the continuous interaction between a projectile and a target material is still commonly assessed with analytical models or numerical simulations, the validation of which is based on the aforementioned discrete values. The present document aims at describing and validating a new experimental method to make it possible to evaluate the continuous evolution of the projectile velocity during penetration into a fabric material. The method is based on the Doppler effect and a specific and complex nonstationary signal treatment. A high-frequency continuous-wave Doppler radar was adapted to assess the continuous evolution of the velocity of a projectile penetrating a fabric material. Based on two ballistic-grade fabric configurations, a perforating and a nonperforating case were described and evaluated. The instantaneous Doppler frequency was extracted based on the Hilbert-Huang transform. A validation of the proposed method was performed based on high-speed camera images, giving the displacement of the apex of the deformation pyramid of the fabric with time. Additionally, a Weibel® Doppler radar was used to measure the impact velocity. Based on instantaneous frequencies deduced from the high-frequency radar signal analysis, Doppler theory and high-speed camera images, velocity–time and displacement–time plots were obtained. Additionally, the evolution of the fabric deformation (pyramid morphology) was recorded from the high-speed camera images. Comparisons between the data assessed with the high-frequency Doppler radar and those deduced from the high-speed camera indicated that good agreement exists between the two methods. The new Doppler radar method seems to be a promising complementary tool for measuring the continuous interaction between a projectile and a fabric target material.

Extraction of Global and Local Micro-Doppler Signature Features From FMCW Radar Returns for UAV Detection

In this article, an unmanned aerial vehicles detection system is proposed for an X-band ground-based surveillance frequency modulated continuous wave Doppler radar. Two novel features are directly extracted from the Doppler processing results without a time-frequency analysis. Experimental results on measured radar echo signals show that our system consistently outperforms the state of the art in terms of detection accuracy and computational efficiency.

A Movement Detection System Using Continuous-Wave Doppler Radar Sensor and Convolutional Neural Network to Detect Cough and Other Gestures.

The 2019 coronavirus disease (COVID-19) pandemic has contaminated millions of people, resulting in high fatality rates. Recently emerging artificial intelligence technologies like the convolutional neural network (CNN) are strengthening the power of imaging tools and can help medical specialists. CNN combined with other sensors creates a new solution to fight COVID-19 transmission. This paper presents a novel method to detect coughs (an important symptom of COVID-19) using a K-band continuous-wave Doppler radar with most popular CNNs architectures: AlexNet, VGG-19, and GoogLeNet. The proposed method has cough detection test accuracy of 88.0% using AlexNet CNN with people 1 m away from the microwave radar sensor, test accuracy of 80.0% with people 3 m away from the radar sensor, and test accuracy of 86.5% with a single mixed dataset with people 1 m and 3 m away from the radar sensor. The K-band radar sensor is inexpensive, completely camera-free and collects no personally-identifying information, allaying privacy concerns while still providing in-depth public health data on individual, local, and national levels. Additionally, the measurements are conducted without human contact, making the process proposed in this work safe for the investigation of contagious diseases such as COVID-19. The proposed cough detection system using microwave radar sensor has environmental robustness and dark/light-independence, unlike traditional cameras. The proposed microwave radar sensor can be used alone or in group with other sensors in a fusion sensor system to create a robust system to detect cough and other movements, mainly if using CNNs.

Vital Sign Detection during Large-Scale and Fast Body Movements Based on an Adaptive Noise Cancellation Algorithm Using a Single Doppler Radar Sensor.

The non-contact detection of human vital signs (i.e., respiration rate (RR) and heartbeat rate (HR)) using a continuous-wave (CW) Doppler radar sensor has great potential for intensive care monitoring, home healthcare, etc. However, large-scale and fast random body movement (RBM) has been a bottleneck for vital sign detection using a single CW Doppler radar. To break this dilemma, this study proposed a scheme combining adaptive noise cancellation (ANC) with polynomial fitting, which could retrieve the weak components of both respiration and heartbeat signals that were submerged under serious RBM interference. In addition, the new-type discrete cosine transform (N-DCT) was introduced to improve the detection accuracy. This scheme was first verified using a numerical simulation. Then, experiments utilizing a 10-GHz Doppler radar sensor that was built from general-purpose radio frequency (RF) and communication instruments were also carried out. No extra RF/microwave components and modules were needed, and neither was a printed circuit board nor an integrated-chip design required. The experimental results showed that both the RR and HR could still be extracted during large-scale and fast body movements using only a single Doppler radar sensor because the RBM noises could be greatly eliminated by utilizing the proposed ANC algorithm.

Fast heart rate extraction using CW Doppler radar with interpolated discrete Fourier transform algorithm

Doppler radar-based fast heart rate (HR) extraction has great application potential in stress and emotion recognition, anxiety treatments, etc. However, fast extraction of HR is still a great challenge for the vital sign detection applying the traditional discrete Fourier transform (DFT) method based on a continuous-wave (CW) Doppler radar sensor. When applying traditional DFT to the baseband signal analysis, the spectrum resolution will become insufficient if the time window is less than 10 s. In this paper, an interpolated DFT algorithm based on a poly-item cosine window is introduced to achieve fast extraction of HR with only 3 s data length. In addition, the leakage and grid effect phenomenon is presented to show the defects caused by the traditional DFT method. To verify the effectiveness of the proposed method, simulations are performed and experiments are executed using a 10-GHz CW Doppler radar sensor platform. Compared with the traditional DFT method, the interpolated DFT method reduces the average HR error from 8.48% to 1.87% based on the Hanning window and from 8.48% to 1.45% based on the rectangular window.

Noncontact Measurement of River Surface Velocity and Discharge Estimation With a Low-Cost Doppler Radar Sensor

River discharge is an important variable to measure in order to predict droughts and flood occurrences. Once the cross-sectional geometry of the river is known, discharge can be inferred from water level and surface flow velocity measurements. Since river discharges are of particular interest during extreme weather events, when river sites cannot be safely accessed, noncontact sensing technologies are particularly appealing. To this purpose, this work proposes a prototype of a low-cost continuous wave (CW) Doppler radar sensor, which is able to monitor the surface flow velocity of rivers. The prototype is tested at two gauged sites in central Italy, along the Tiber River. The surface flow velocity distribution across the river is monitored by means of the analysis of received Doppler signal. The surface velocity statistics are then extracted using a novel algorithm that is optimized to run on a microprocessor platform with minimal computing power (ArduinoUNO). In particular, the radar measurements are used to initialize a 2-D entropy-based velocity model (EVM) that is able to estimate river discharges in any flow condition. Finally, the results concerning the observed discharge provided by the EVM prove to be comparable with those obtained with more expensive commercial solutions. The results are important since the described methodology can be extended to small-size Doppler radar sensors onboard unmanned aerial vehicles (UAVs), the latter providing a method for mapping surface velocity of rivers.