Impulse Radio Ultra-wideband Radar Research Articles

Lane Detection Method with Impulse Radio Ultra-Wideband Radar and Metal Lane Reflectors.

An advanced driver-assistance system (ADAS), based on lane detection technology, detects dangerous situations through various sensors and either warns the driver or takes over direct control of the vehicle. At present, cameras are commonly used for lane detection; however, their performance varies widely depending on the lighting conditions. Consequently, many studies have focused on using radar for lane detection. However, when using radar, it is difficult to distinguish between the plain road surface and painted lane markers, necessitating the use of radar reflectors for guidance. Previous studies have used long-range radars which may receive interference signals from various objects, including other vehicles, pedestrians, and buildings, thereby hampering lane detection. Therefore, we propose a lane detection method that uses an impulse radio ultra-wideband radar with high-range resolution and metal lane markers installed at regular intervals on the road. Lane detection and departure is realized upon using the periodically reflected signals as well as vehicle speed data as inputs. For verification, a field test was conducted by attaching radar to a vehicle and installing metal lane markers on the road. Experimental scenarios were established by varying the position and movement of the vehicle, and it was demonstrated that the proposed method enables lane detection based on the data measured.

Robust Detection of Presence of Individuals in an Indoor Environment Using IR-UWB Radar

In this paper, we propose a robust detection method to determine the presence of individuals in an indoor environment by exploiting an impulse-radio ultra-wideband (IR-UWB) radar. Detection of the presence of individuals in an indoor environment using IR-UWB is not a trivial problem because real indoor environments provide heavy clutter components and spurious ones due to multipath effects. The study mainly discusses two difficulties involved in detecting an individual in an indoor environment, namely, how to reduce the clutter in an indoor environment and how to detect a very low radar cross section (RCS) target, i.e., an individual lying down. To reduce clutter components in indoor environments, we investigated several clutter reduction techniques in terms of detecting a standing individual and an individual lying down. However, even after clutter reduction, detection of an individual lying down continues to pose a challenge. Thus, we devised a novel two-stage detection scheme that first involves detection in the range domain, and then in the frequency domain, thereby resulting in good detection performance in terms of a high detection rate and a low false alarm rate. The proposed method was demonstrated by experiments in indoor environments, and the results indicate that its performance is robust in various scenarios.

In-Air Continuous Writing Using UWB Impulse Radar Sensors

We developed an impulse radio ultra-wideband (IR-UWB) radar-based system that can recognize alphanumeric characters in midair without the need for any handheld device. The hardware consists of four IR-UWB radar sensors set up with a rectangular geometry. Writing a single character in midair results in artifacts that make some characters look similar on a position trajectory-based (x, y) plane, which makes them difficult to classify. Thus, we developed an algorithm that transforms 2D coordinate image data into trigonometric ratios (i.e., tangents) and plots them against the time axis to obtain unique images for training a convolutional neural network. An extended Kalman filter is used to obtain the 2D trajectories of hand motions. To evaluate our proposed method, we first applied it to characters that may be written in midair very simply without creating artifacts and compared its performance with that of a state-of-the-art digit classification algorithm. Then, we considered combining characters written midair with and without artifacts. After the individual character recognition, we combined the characters into words. We defined a specific marker based on an energy threshold to detect the start and end of a character for midair writing. The energy level was found to change drastically when the hand is pulled in and out of the radar plane. The proposed method was found to outperform the current state of the art at character classification when artifacts are present in the images.

효율적인 신호분리기법을 이용한 근접한 두 사람들의 비접촉식 생체신호 탐지

Recently, non-contact vital sign(i.e. respiratory and cardiac rate) detection(VSD) techniques based on radar sensors have been developed for several applications in the medical, Internet of Things(IoT), and military fields. However, if two humans are located at the same distance, the VSD of these methods may fail. This is because the two humans yield mixed and complicated echo signals, thereby making the VSD task quite difficult. To overcome this problem, several signal decomposition methods, such as variational mode decomposition and multiple signal classification, have been developed. Nevertheless, mixed echo signals from two humans at the same distance cannot be decomposed. In this study, we propose a new signal decomposition method to achieve the VSD of humans at the same distance. In particular, the proposed method can simply decompose I- and Q-channel parts of a mixed echo signal into the individual phase fluctuations corresponding to each human, thereby providing improved computational efficiency. In experiments using the impulse-radio ultra-wideband radar, it was observed that the proposed algorithm can successfully achieve the VSD of two humans at the same distance.

Method for Distinguishing Humans and Animals in Vital Signs Monitoring Using IR-UWB Radar.

Radar has been widely applied in many scenarios as a critical remote sensing tool for non-contact vital sign monitoring, particularly for sleep monitoring and heart rate measurement within the home environment. For non-contact monitoring with radar, interference from house pets is an important issue that has been neglected in the past. Many animals have respiratory frequencies similar to those of humans, and they are easily mistaken for human targets in non-contact monitoring, which would trigger a false alarm because of incorrect physiological parameters from the animal. In this study, humans and common pets in families, such as dogs, cats, and rabbits, were detected using an impulse radio ultrawideband (IR-UWB) radar, and the echo signals were analyzed in the time and frequency domains. Subsequently, based on the distinct in-body structure between humans and animals, we propose a parameter, the respiratory and heartbeat energy ratio (RHER), which reflects the contribution rate of breathing and heartbeat in the detected vital signs. Combining this parameter with the energy index, we developed a novel scheme to distinguish between humans and animals. In the developed scheme, after background noise removal and direct-current component suppression, an energy indicator is used to initially identify the target. The signal is then decomposed using a variational mode decomposition algorithm, and the variational intrinsic mode functions that represent human respiration and heartbeat components are obtained and utilized to calculate the RHER parameter. Finally, the RHER index is applied to rapidly distinguish between humans and animals. Our experimental results demonstrate that the proposed approach more effectively distinguishes between humans and animals in terms of monitoring vital signs than the existing methods. Furthermore, its rapidity and need for only minimal calculation resources enable it to meet the needs of real-time monitoring.

A Multiple Target Positioning and Tracking System Behind Brick-Concrete Walls Using Multiple Monostatic IR-UWB Radars.

Recognizing and tracking the targets located behind walls through impulse radio ultra-wideband (IR-UWB) radar provides a significant advantage, as the characteristics of the IR-UWB radar signal enable it to penetrate obstacles. In this study, we design a through-wall radar system to estimate and track multiple targets behind a wall. The radar signal received through the wall experiences distortion, such as attenuation and delay, and the characteristics of the wall are estimated to compensate the distance error. In addition, unlike general cases, it is difficult to maintain a high detection rate and low false alarm rate in this through-wall radar application due to the attenuation and distortion caused by the wall. In particular, the generally used delay-and-sum algorithm is significantly affected by the motion of targets and distortion caused by the wall, rendering it difficult to obtain a good performance. Thus, we propose a novel method, which calculates the likelihood that a target exists in a certain location through a detection process. Unlike the delay-and-sum algorithm, this method does not use the radar signal directly. Simulations and experiments are conducted in different cases to show the validity of our through-wall radar system. The results obtained by using the proposed algorithm as well as delay-and-sum and trilateration are compared in terms of the detection rate, false alarm rate, and positioning error.

Preclinical Evaluation of a Noncontact Simultaneous Monitoring Method for Respiration and Carotid Pulsation Using Impulse-Radio Ultra-Wideband Radar

There has been the possibility for respiration and carotid pulsation to be simultaneously monitored from a distance using impulse-radio ultra-wideband (IR-UWB) radar. Therefore, we investigated the validity of simultaneous respiratory rates (RR), pulse rates (PR) and R-R interval measurement using IR-UWB radar. We included 19 patients with a normal sinus rhythm (NSR) and 14 patients with persistent atrial fibrillation (PeAF). The RR, PR, R-R interval and rhythm were obtained simultaneously from the right carotid artery area in a supine position and under normal breathing conditions using IR-UWB radar. There was excellent agreement between the RR obtained by IR-UWB radar and that manually counted by a physician (intraclass correlation coefficient [ICC] 0.852). In the NSR group, there was excellent agreement between the PR (ICC 0.985), average R-R interval (ICC 0.999), and individual R-R interval (ICC 0.910) measured by IR-UWB radar and electrocardiography. In the PeAF group, PR (ICC 0.930), average R-R interval (ICC 0.957) and individual R-R interval (ICC 0.701) also agreed well between the two methods. These results demonstrate that IR-UWB radar can simultaneously monitor respiration, carotid pulse and heart rhythm with high precision and may thus be utilized as a noncontact continuous vital sign monitoring in clinical practice.

Validation of noncontact cardiorespiratory monitoring using impulse-radio ultra-wideband radar against nocturnal polysomnography

Polysomnography (PSG) is a standard diagnostic test for obstructive sleep apnea (OSA). However, PSG requires many skin-contacted sensors to monitor vital signs of patients, which may also hamper patients' sleep. Because impulse-radio ultra-wideband (IR-UWB) radar can detect the movements of heart and lungs without contact, it may be utilized for vital sign monitoring during sleep. Therefore, we aimed to verify the accuracy and reliability of the breathing rate (BR) and the heart rate (HR) measured by IR-UWB radar. Data acquisition with PSG and IR-UWB radar was performed simultaneously in 6 healthy volunteers and in 15 patients with suspected OSA. Subjects were divided into 4 groups (normal, mild OSA, moderate OSA, and severe OSA) according to the apnea-hypopnea index (AHI). BRs and HRs obtained from the radar using a software algorithm were compared with the BRs (chest belt) and the HRs (electrocardiography) obtained from the PSG. In normal and in mild OSA, BRs (intraclass correlation coefficients R [ICCR] 0.959 [0.956-0.961] and 0.957 [0.955-0.960], respectively) and HRs ([ICCR] 0.927 [0.922-0.931] and 0.926 [0.922-0.931], respectively) measured in the radar showed excellent agreement with those measured in PSG. In moderate and severe OSA, BRs ([ICCR] 0.957 [0.956-0.959] and 0.873 [0.864-0.882], respectively) and HRs ([ICCR] 0.907 [0.904-0.910] and 0.799 [0.784-0.812], respectively) from the two methods also agreed well. The IR-UWB radar could accurately measure BRs and HRs in sleeping patients with OSA. Therefore, IR-UWB radar may be utilized as a cardiopulmonary monitor during sleep.

A weighted least squares consideration for IR-UWB radar based device-free object positioning estimation for indoor environment

<p>Impulse Radio Ultra-Wideband (IR-UWB) radar is a type of radar functioning based on UWB transmission technology that uses an exceedingly wide bandwidth low power impulse signal to continuously transmitting and receiving the impulse signal for object detection within a range. To date, most of the proposed Ultra-Wideband (UWB) transmission technology based object positioning estimation systems for indoor environment depends on objects to be attached with an active UWB devices. In certain circumstances, it is ideal to track objects in passive manner without the requirement of any attached tracking devices or device-free object positioning estimation. IR-UWB radar has shown promising utilization in realizing device-free object positioning estimation for indoor environment. With this motivation, in this paper a work on weighted least squares consideration for IR-UWB radar based device-free object positioning estimation for indoor environment is presented.</p>

Analysis of Beamforming Antenna for Practical Indoor Location-Tracking Application.

The single antenna used in conventional ultra-wideband radar has difficulty tracking targets over a wide range because of a relatively narrow beamwidth. Herein, we propose a beamforming antenna that can track targets over a wide range by electronically controlling the main beam of the antenna. The proposed beamforming antenna was fabricated by connecting a 1 × 4 linear array antenna and a 4 × 4 Butler matrix. The Butler matrix was fabricated in a laminated substrate using two TRF-45 substrates. Furthermore, the input Ports 1–4 generate a phase difference at regular intervals in each output port, and the output phase is fed to the array antenna. The proposed tapered-slot antenna was fabricated on a Taconic TLY substrate, and the impedance bandwidth of the antenna was achieved within a wide bandwidth of 4.32 GHz by satisfying a VSWR (Voltage Standing Wave Ratio) ≤2 within the 1.45–5.78 GHz band. Furthermore, the fabricated antenna has directional radiation patterns, which was found to be a suitable characsteristic for location tracking in a certain direction. Finally, the beamforming antenna has four beamforming angles, and to verify the performance for an indoor location tracking application of impulse-radio ultra-wideband radar, it was connected to an NVA-R661 module.

Non-contact respiration monitoring using impulse radio ultrawideband radar in neonates.

Vital sign monitoring in neonates requires adhesive electrodes, which often damage fragile newborn skin. Because impulse radio ultrawideband (IR-UWB) radar has been reported to recognize chest movement without contact in adult humans, IR-UWB may be used to measure respiratory rates (RRs) in a non-contact fashion. We investigated the feasibility of radar sensors for respiration monitoring in neonates without any respiratory support to compare the accuracy and reliability of radar measurements with those of conventional impedance pneumography measurements. In the neonatal intensive care unit, RRs were measured using radar (RRRd) and impedance pneumography (RRIP) simultaneously. The neonatal voluntary movements were measured using the radar sensor and categorized into three levels (low [M0], intermediate [M1] and high [M2]). RRRd highly agreed with RRIP (r = 0.90; intraclass correlation coefficient [ICC] = 0.846 [0.835–0.856]). For the M0 movement, there was good agreement between RRRd and RRIP (ICC = 0.893; mean bias −0.15 [limits of agreement (LOA) −9.6 to 10.0]). However, the agreement was slightly lower for the M1 (ICC = 0.833; mean bias = 0.95 [LOA −11.4 to 13.3]) and M2 (ICC = 0.749; mean bias = 3.04 [LOA –9.30 to 15.4]) movements than for the M0 movement. In conclusion, IR-UWB radar can provide accurate and reliable estimates of RR in neonates in a non-contact fashion. The performance of radar measurements could be affected by neonate movement.

Distance Estimation Scheme Exploiting IR-UWB Radar with Clutter Suppressing Algorithm in Indoor Environments

This paper proposes a distance estimation scheme with an impulse radio ultrawide-band (IR-UWB) radar for a long-range target in an indoor environment. When the pulse is transmitted from the IR-UWB radar and is reflected from the target, fading effects make it difficult to estimate the time-of-arrival of a direct path, which can be distorted by the clutter in indoor environments. The proposed scheme can improve the performance of distance estimation by mitigating the effect of the clutter with a low-rank approximation scheme and a singular value decomposition scheme. The performance of the proposed scheme is evaluated through experiments in a general office building, and the results of the experiment show that the proposed scheme can track the dynamic distance of a target from the radar up to 11 m in an open space and 14 m in a narrow corridor, respectively, with an average error of less than 0.2 m.

원하지 않는 작은 동작에 의한 잡음 환경 내 생체신호 탐지 기법

Recently, many studies on vital sign detection using a radar sensor related to Internet of Things(IoT) smart home systems have been conducted. Because vital signs such as respiration and cardiac rates generally cause micro-motions in the chest or back, the phase of the received echo signal from a target fluctuates according to the micro-motion. Therefore, vital signs are usually detected via spectral analysis of the phase. However, the probability of false alarms in cardiac rate detection increases as a result of various problems in the measurement environment, such as very weak phase fluctuations caused by the cardiac rate. Therefore, this study analyzes the difficulties of vital sign detection and proposes an efficient vital sign detection algorithm consisting of four main stages: 1) phase decomposition, 2) phase differentiation and filtering, 3) vital sign detection, and 4) reduction of the probability of false alarm. Experimental results using impulse-radio ultra-wideband radar show that the proposed algorithm is very efficient in terms of computation and accuracy.

Quantified Activity Measurement for Medical Use in Movement Disorders through IR-UWB Radar Sensor.

Movement disorders, such as Parkinson’s disease, dystonia, tic disorder, and attention-deficit/hyperactivity disorder (ADHD) are clinical syndromes with either an excess of movement or a paucity of voluntary and involuntary movements. As the assessment of most movement disorders depends on subjective rating scales and clinical observations, the objective quantification of activity remains a challenging area. The purpose of our study was to verify whether an impulse radio ultra-wideband (IR-UWB) radar sensor technique is useful for an objective measurement of activity. Thus, we proposed an activity measurement algorithm and quantitative activity indicators for clinical assistance, based on IR-UWB radar sensors. The received signals of the sensor are sufficiently sensitive to measure heart rate, and multiple sensors can be used together to track the positions of people. To measure activity using these two features, we divided movement into two categories. For verification, we divided these into several scenarios, depending on the amount of activity, and compared with an actigraphy sensor to confirm the clinical feasibility of the proposed indicators. The experimental environment is similar to the environment of the comprehensive attention test (CAT), but with the inclusion of the IR-UWB radar. The experiment was carried out, according to a predefined scenario. Experiments demonstrate that the proposed indicators can measure movement quantitatively, and can be used as a quantified index to clinically record and compare patient activity. Therefore, this study suggests the possibility of clinical application of radar sensors for standardized diagnosis.

Noncontact Heart Rate Measurement Based on an Improved Convolutional Sparse Coding Method Using IR-UWB Radar

Impulse radio ultrawideband radar is a critical remote sensing tool for life detection and noncontact monitoring of vital signals. In noncontact monitoring via radar, the disturbance from respiration and environmental noise is considered critical for the estimation of heart rates. However, the heartbeat signal is generally distorted by breath harmonics and fluctuations in the time domain, and the frequencies of the vital signals are closely situated; thus, it is difficult to employ an ordinary frequency filter for separation. To solve this problem, a novel method was developed to extract heartbeat information. In this study, convolutional sparse coding, which is an unsupervised machine learning algorithm, was first used to model the heartbeat signal in the time domain, given the respiration and relative artifacts. The proposed scheme was then used to decompose the time-domain signals and directly obtain the heartbeat component by exploiting the sparsity of the heartbeat signal in the time domain. Furthermore, the performance of the proposed scheme was improved using a noise-assisted method, and the process was accelerated by learning from the K-singular value decomposition strategy. Finally, by testing the vital sign signals collected from the finite differences time-domain simulation and experiments, the results obtained indicate that the proposed approach is effective for the extraction of low-amplitude heartbeat signals from the respiration signal, and that it significantly improves the accuracy of heart rate evaluation.

Respiration and Heartbeat Rates Measurement Based on Autocorrelation Using IR-UWB Radar

Respiration rate (RR) and heartbeat rate (HR) are important physiological parameters for a person. Impulse radio ultra-wideband (IR-UWB) is a promising technology for non-contact sensing and monitoring. This brief presents a new method based on autocorrelation to measure the RR and HR using IR-UWB radar. The correlation coefficient waveform contains the vital sign signals, overcoming the effect of noise and clutter. Applying fast Fourier transform, the respiration frequency can be acquired easily. A clever method also based on autocorrelation is proposed to locate the subject. The receive signal matrix is divided into a set of bins in the direction of fast time. By removing one block from the matrix each time and re-applying the autocorrelation, the removed block resulting the smallest correlations is corresponding to the location of a subject. Moreover, variational mode decomposition algorithm is adopted to successfully separate the respiration and heartbeat signals. Experiments are carried out using a PulsOn410 UWB radar. The results show that the proposed low-complexity algorithm has high accuracy.

HEAR: Approach for Heartbeat Monitoring with Body Movement Compensation by IR-UWB Radar.

Further applications of impulse radio ultra-wideband radar in mobile health are hindered by the difficulty in extracting such vital signals as heartbeats from moving targets. Although the empirical mode decomposition based method is applied in recovering waveforms of heartbeats and estimating heart rates, the instantaneous heart rate is not achievable. This paper proposes a Heartbeat Estimation And Recovery (HEAR) approach to expand the application to mobile scenarios and extract instantaneous heartbeats. Firstly, the HEAR approach acquires vital signals by mapping maximum echo amplitudes to the fast time delay and compensating large body movements. Secondly, HEAR adopts the variational nonlinear chirp mode decomposition in extracting instantaneous frequencies of heartbeats. Thirdly, HEAR extends the clutter removal method based on the wavelet decomposition with a two-parameter exponential threshold. Compared to heart rates simultaneously collected by electrocardiograms (ECG), HEAR achieves a minimum error rate 4.6% in moving state and 2.25% in resting state. The Bland–Altman analysis verifies the consistency of beat-to-beat intervals in ECG and extracted heartbeat signals with the mean deviation smaller than 0.1 s. It indicates that HEAR is practical in offering clinical diagnoses such as the heart rate variability analysis in mobile monitoring.

A Novel Non-contact Heart Rate Monitor Using Impulse-Radio Ultra-Wideband (IR-UWB) Radar Technology

We discovered that impulse-radio ultra-wideband (IR-UWB) radar could recognize cardiac motions in a non-contact fashion. Therefore, we measured the heart rate (HR) and rhythms using an IR-UWB radar sensor and evaluated the validity and reliability of the measurements in comparison to electrocardiography. The heart beats were measured in 6 healthy volunteers (18 samples) with normal sinus rhythm (NSR) and 16 patients (36 samples) with atrial fibrillation (AF) using both an IR-UWB radar sensor and electrocardiography simultaneously. The participants hold their breath for 20 seconds during the data acquisition. In subjects with NSR, there was excellent agreement of HR (intraclass correlation coefficient [ICC] 0.856), average R-R interval (ICC 0.997) and individual R-R intervals between the two methods (ICC 0.803). In subjects with AF, HR (ICC 0.871) and average R-R interval (ICC 0.925) from the radar sensor also agreed well with those from electrocardiography, though there was a small disagreement in the individual R-R intervals between the two methods (ICC 0.697). The rhythms computed by the signal-processing algorithm showed good agreement between the two methods (Cohen’s Kappa 0.922). The IR-UWB radar sensor is precise and accurate for assessing HR and rhythms in a non-contact fashion.

Self-adjustable domain adaptation in personalized ECG monitoring integrated with IR-UWB radar

Abstract To enhance electrocardiogram (ECG) monitoring systems in personalized detections, deep neural networks (DNNs) are applied to overcome individual differences by periodical retraining. As introduced previously [4] , DNNs relieve individual differences by fusing ECG with impulse radio ultra-wide band (IR-UWB) radar. However, such DNN-based ECG monitoring system tends to overfit into personal small datasets and is difficult to generalize to newly collected unlabeled data. This paper proposes a self-adjustable domain adaptation (SADA) strategy to prevent from overfitting and exploit unlabeled data. Firstly, this paper enlarges the database of ECG and radar data with actual records acquired from 28 testers and expanded by the data augmentation. Secondly, to utilize unlabeled data, SADA combines self organizing maps with the transfer learning in predicting labels. Thirdly, SADA integrates the one-class classification with domain adaptation algorithms to reduce overfitting. Based on our enlarged database and standard databases, a large dataset of 73200 records and a small one of 1849 records are built up to verify our proposal. Results show SADA's effectiveness in predicting labels and increments in the sensitivity of DNNs by 14.4% compared with existing domain adaptation algorithms.

A Pilot Study of Impulse Radio Ultra Wideband Radar Technology as a New Tool for Sleep Assessment.

To validate Impulse radio ultra wideband pulse-doppler radar technology against polysomnography (PSG) for sleep assessment. In all, 12 participants were recruited and their overnight sleep was assessed both by a Novelda XeThru radar and PSG. Two subjects had two nightly recordings, whereas 10 had one recording. Epoch by epoch (30 seconds) comparisons from bedtime to rise time were conducted. Concordance was estimated in terms of the mean difference between the radar and the PSG estimates regarding sleep onset latency, wake time after sleep onset and total sleep time. In addition, accuracy, sensitivity, specificity and Cohen kappa were calculated. The mean difference (minutes) between the radar and the PSG registrations was -5.7 minutes (standard deviation [SD] = 22.1 minutes) for sleep onset latency, 6.4 minutes (SD = 32.5 minutes) for wake after sleep onset, and 1.5 minutes (SD = 24.6 minutes) for total sleep time. The mean values obtained for accuracy, sensitivity, specificity and Cohen kappa were 0.931, 0.961, 0.695 and 0.670, respectively. Impulse radio ultra wideband radar technology is a promising tool in terms of affordable and practical objective sleep assessment. Further technical development and more validation studies are needed in order to conclude about the utility potential of this device.