A Combined UWB/IMU Localization Method with Improved CKF.

Aiming at the problem that ultra-wide band (UWB) cannot be accurately localized in environments with large noise variations and unknown statistical properties, a combinatorial localization method based on improved cubature (CKF) is proposed. First, in order to overcome the problem of inaccurate local approximation or even the inability to converge due to the initial value not being set near the optimal solution in the process of solving the UWB position by the least-squares method, the Levenberg-Marquardt algorithm (L-M) is adopted to optimally solve the UWB position. Secondly, because UWB and IMU information are centrally fused, an adaptive factor is introduced to update the measurement noise covariance matrix in real time to update the observation noise, and the fading factor is added to suppress the filtering divergence to achieve an improvement for the traditional CKF algorithm. Finally, the performance of the proposed combined localization method is verified by field experiments in line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios, respectively. The results show that the proposed method can maintain high localization accuracy in both LOS and NLOS scenarios. Compared with the Extended Kalman filter (EKF), unbiased Kalman filter (UKF), and CKF algorithms, the localization accuracies of the proposed method in NLOS scenarios are improved by 25.2%, 18.3%, and 11.3%, respectively.

MIC: Microwave Imaging Curtain for Dynamic and Automatic Detection of Weapons and Explosive Belts.

DEXTER (detection of explosives and firearms to counter terrorism) is a project funded by NATO's Science for Peace and Security (SPS) program with the goal of developing an integrated system capable of remotely and accurately detecting explosives and firearms in public places without impeding the flow of pedestrians. While body scanner systems in secure areas of public places are becoming more and more efficient, the attack at Brussels airport on 22 March 2016, upstream of these systems, in the middle of the crowd of passengers, demonstrated the lack of discreet and real-time security against threats of mass terrorism. The NATO-SPS international and multi-year DEXTER project aims to provide new technical and strategic solutions to fill this gap. This project is based on multi-sensor coordination and fusion, from hyperspectral remote laser to smart glasses, artificial algorithms, and suspect identification and tracking. One of these sensors is dedicated to threat detection (large weapon or explosive belt) using the clothing of pedestrians by means of an active microwave component. This project is referred to as MIC (Microwave Imaging Curtain), also supported by the French SGDSN (General Secretariat of Defense and National Security), and utilizes a radar system capable of generating 3D images in real-time to address non-checkpoint detection of explosives and firearms. The project, led by ONERA (France), is based on a radar imaging system developed by the Fraunhofer FHR institute, using a MIMO architecture with an Ultra-Wide Band waveform. Although high-resolution 3D microwave imaging is already being used in expensive body scanners to detect firearms concealed under clothing, MIC's innovative approach lies in utilizing a high-resolution 3D imaging device that can detect larger dangerous objects carried by moving individuals at a longer range, in addition to providing discrete detection in pedestrian flow. Automatic detection and classification of these dangerous objects is carried out on 3D radar images using a deep-learning network. This paper will outline the project's objectives and constraints, as well as the design, architecture, and performance of the final system. Additionally, it will present real-time imaging results obtained during a live demonstration in a relevant environment.

An Improved UWB/IMU Tightly Coupled Positioning Algorithm Study.

The combination of ultra-wide band (UWB) and inertial measurement unit (IMU) positioning is subject to random errors and non-line-of-sight errors, and in this paper, an improved positioning strategy is proposed to address this problem. The Kalman filter (KF) is used to pre-process the original UWB measurements, suppressing the effect of range mutation values of UWB on combined positioning, and the extended Kalman filter (EKF) is used to fuse the UWB measurements with the IMU measurements, with the difference between the two measurements used as the measurement information. The non-line-of-sight (NLOS) measurement information is also used. The optimal estimate is obtained by adjusting the system measurement noise covariance matrix in real time, according to the judgment result, and suppressing the interference of non-line-of-sight factors. The optimal estimate of the current state is fed back to the UWB range value in the next state, and the range value is dynamically adjusted after one-dimensional filtering pre-processing. Compared with conventional tightly coupled positioning, the positioning accuracy of the method in this paper is improved by 46.15% in the field experimental positioning results.

Antenna Arrangement in UWB Helmet Brain Applicators for Deep Microwave Hyperthermia.

Deep microwave hyperthermia applicators are typically designed as narrow-band conformal antenna arrays with equally spaced elements, arranged in one or more rings. This solution, while adequate for most body regions, might be sub-optimal for brain treatments. The introduction of ultra-wide-band semi-spherical applicators, with elements arranged around the head and not necessarily aligned, has the potential to enhance the selective thermal dose delivery in this challenging anatomical region. However, the additional degrees of freedom in this design make the problem non-trivial. We address this by treating the antenna arrangement as a global SAR-based optimization process aiming at maximizing target coverage and hot-spot suppression in a given patient. To enable the quick evaluation of a certain arrangement, we propose a novel E-field interpolation technique which calculates the field generated by an antenna at any location around the scalp from a limited number of initial simulations. We evaluate the approximation error against full array simulations. We demonstrate the design technique in the optimization of a helmet applicator for the treatment of a medulloblastoma in a paediatric patient. The optimized applicator achieves 0.3 °C higher T90 than a conventional ring applicator with the same number of elements.

Ultra-Wide Band Gap Ga2O3-on-SiC MOSFETs.

Ultra-wide band gap semiconductor devices based on ß-phase gallium oxide (Ga2O3) offer the potential to achieve higher switching performance and efficiency and lower manufacturing cost than that of today's wide band gap power electronics. However, the most critical challenge to the commercialization of Ga2O3 electronics is overheating, which impacts the device performance and reliability. We fabricated a Ga2O3/4H-SiC composite wafer using a fusion-bonding method. A low-temperature (≤600 °C) epitaxy and device processing scheme was developed to fabricate MOSFETs on the composite wafer. The low-temperature-grown epitaxial Ga2O3 devices deliver high thermal performance (56% reduction in channel temperature) and a power figure of merit of (∼300 MW/cm2), which is the highest among heterogeneously integrated Ga2O3 devices reported to date. Simulations calibrated based on thermal characterization results of the Ga2O3-on-SiC MOSFET reveal that a Ga2O3/diamond composite wafer with a reduced Ga2O3 thickness (∼1 µm) and a thinner bonding interlayer (<10 nm) can reduce the device thermal impedance to a level lower than that of today's GaN-on-SiC power switches.

Analysis of key external and internal load variables in professional female futsal players: a longitudinal study.

The aims of this study were to identify the key external and internal load variables in professional futsal through principal components analysis (PCA), and analyse the physical performance required by the players in official matches. Data were collected from 14 female players during 10 matches using WIMU PROTM. The PCA selected a total of 22 variables as key indicators of players' load. Specifically, these variables were represented by five principal components. However, a novel finding was that different components were extracted when the analysis was carried out by full match (68.83% of total variance), first half (69.81% of total variance), or second half (65.96% of total variance). Also, this study found that the players decreased their physical performance during the second half. Based on these results, this study may help optimize performance and reduce the injury risk. Performance should not be only analysed considering the full match external/internal load but also specifying by match halves. This is explained by the fact that there were variables that made up the principal components in the first half, but not in the second half or full match. Finally, coaches should adopt training strategies which deal with the decrease in physical performance during the second half.

Effects of Boron Doping on the Bulk and Surface Acoustic Phonons in Single-Crystal Diamond.

We report the results of the investigation of bulk and surface acoustic phonons in the undoped and boron-doped single-crystal diamond films using the Brillouin-Mandelstam light scattering spectroscopy. The evolution of the optical phonons in the same set of samples was monitored with Raman spectroscopy. It was found that the frequency and the group velocity of acoustic phonons decrease nonmonotonically with the increasing boron doping concentration, revealing pronounced phonon softening. The change in the velocity of the shear-horizontal and the high-frequency pseudo-longitudinal acoustic phonons in the degenerately doped diamond, as compared to that in the undoped diamond, was as large as ∼15% and ∼12%, respectively. As a result of boron doping, the velocity of the bulk longitudinal and transverse acoustic phonons decreased correspondingly. The frequency of the optical phonons was unaffected at low boron concentration but experienced a strong decrease at the high doping level. The density-functional-theory calculations of the phonon band structure for the pristine and highly doped samples confirm the phonon softening as a result of boron doping in diamond. The obtained results have important implications for thermal transport in heavily doped diamond, which is a promising material for ultra-wide-band-gap electronics.

Properties for Thermally Conductive Interfaces with Wide Band Gap Materials.

The goal of this study is to determine how bulk vibrational properties and interfacial structure affect thermal transport at interfaces in wide band gap semiconductor systems. Time-domain thermoreflectance measurements of thermal conductance G are reported for interfaces between nitride metals and group IV (diamond, SiC, Si, and Ge) and group III-V (AlN, GaN, and cubic BN) materials. Group IV and group III-V semiconductors have systematic differences in vibrational properties. Similarly, HfN and TiN are also vibrationally distinct from each other. Therefore, comparing G of interfaces formed from these materials provides a systematic test of how vibrational similarity between two materials affects interfacial transport. For HfN interfaces, we observe conductances between 140 and 300 MW m-2 K-1, whereas conductances between 200 and 800 MW m-2 K-1 are observed for TiN interfaces. TiN forms exceptionally conductive interfaces with GaN, AlN, and diamond, that is, G > 400 MW m-2 K-1. Surprisingly, interfaces formed between vibrationally similar and dissimilar materials are similarly conductive. Thus, vibrational similarity between two materials is not a necessary requirement for high G. Instead, the time-domain thermoreflectance experiment (TDTR) data, an analysis of bulk vibrational properties, and transmission electron microscopy (TEM) suggest that G depends on two other material properties, namely, the bulk phonon properties of the vibrationally softer of the two materials and the interfacial structure. To determine how G depends on interfacial structure, TDTR and TEM measurements were conducted on a series of TiN/AlN samples prepared in different ways. Interfacial disorder at a TiN/AlN interface adds a thermal resistance equivalent to ∼1 nm of amorphous material. Our findings improve fundamental understanding of what material properties are most important for thermally conductive interfaces. They also provide benchmarks for the thermal conductance of interfaces with wide band gap semiconductors.

Design and Implementation of Real-Time Localization System (RTLS) Based on UWB and TDoA Algorithm.

Nowadays, accurate localization plays an essential role in many fields, such as target tracking and path planning. The challenges of indoor localization include inadequate localization accuracy, unreasonable anchor deployment in complex scenarios, lack of stability, and the high cost. So, the universal positioning technologies cannot meet the real application requirements scarcely. To overcome these shortcomings, a comprehensive ultra wide-band (UWB)-based real-time localization system (RTLS) is presented in this paper. We introduce the architecture of a real-time localization system, then propose a new wireless clock synchronization (WCS) scheme, and finally discuss the time difference of arrival (TDoA) algorithm. We define the time-base selection strategy for the TDoA algorithm, and we analyze the relationship between anchor deployment and positioning accuracy. The extended Kalman filter (EKF) method is presented for non-linear dynamic localization estimation, and it performs well in terms of stability and accuracy on moving targets.

Frequency Selective Surface for Ultra-Wide Band Filtering and Shielding.

A frequency selective surface for spatial filtering in the standardized Ultra-Wide Band (UWB) frequency range is proposed. A very large stop-band of 1.75-15.44 GHz has been obtained, with good polarization insensitivity and an angular stability of more than 60∘ and more than 50∘ in TE and TM incidence, respectively. Circuit models have been devised. The structure has been assessed by electromagnetic simulation and implemented on an FR4 substrate of 1.6 mm thickness, with an edge of the square-shaped unit cell of 15 mm. Tests in an anechoic chamber demonstrated good matching between simulation and experimental results and proper operation of the device.

Application of Ultra-Wide Band Sensors in Mining.

Ultra-wideband (UWB) sensors are a radio frequency technology that use wireless communication between devices to precisely determine the position. The most recent applications focus on locating and sensor data collecting on mobile phones, car keys and other similar devices. However, this technology is still not being utilized in the mining sector. To overcome this gap, this perspective offers implementation options and solutions. Additionally, it evaluated the benefits and drawbacks of using ultra-wideband for mining. The measurements provided were made using QORVO two-way ranging sensors, and these were compared to theoretical and existing technological solutions. To ensure the optimal use of UWB sensors, a special emphasis was placed on certain influencing factors, such as ways of locating via UWB and factors affecting measurement accuracies, such as the line of sight, multipath propagation, the effect of shielding and the ideal measurement setup. A conducted experiment showed that the most accurate results are obtained when there is no multipath propagation and the arriving signal travels directly from the transmitter to the receiver.

A Novel Hybrid NN-ABPE-Based Calibration Method for Improving Accuracy of Lateration Positioning System.

Positioning systems based on the lateration method utilize distance measurements and the knowledge of the location of the beacons to estimate the position of the target object. Although most of the global positioning techniques rely on beacons whose locations are known a priori, miscellaneous factors and disturbances such as obstacles, reflections, signal propagation speed, the orientation of antennas, measurement offsets of the beacons hardware, electromagnetic noise, or delays can affect the measurement accuracy. In this paper, we propose a novel hybrid calibration method based on Neural Networks (NN) and Apparent Beacon Position Estimation (ABPE) to improve the accuracy of a lateration positioning system. The main idea of the proposed method is to use a two-step position correction pipeline that first performs the ABPE step to estimate the perceived positions of the beacons that are used in the standard position estimation algorithm and then corrects these initial estimates by filtering them with a multi-layer feed-forward neural network in the second step. In order to find an optimal neural network, 16 NN architectures with 10 learning algorithms and 12 different activation functions for hidden layers were implemented and tested in the MATLAB environment. The best training outcomes for NNs were then employed in two real-world indoor scenarios: without and with obstacles. With the aim to validate the proposed methodology in a scenario where a fast set-up of the system is desired, we tested eight different uniform sampling patterns to establish the influence of the number of the training samples on the accuracy of the system. The experimental results show that the proposed hybrid NN-ABPE method can achieve a high level of accuracy even in scenarios when a small number of calibration reference points are measured.

Respiration Based Non-Invasive Approach for Emotion Recognition Using Impulse Radio Ultra Wide Band Radar and Machine Learning.

Emotion recognition gained increasingly prominent attraction from a multitude of fields recently due to their wide use in human-computer interaction interface, therapy, and advanced robotics, etc. Human speech, gestures, facial expressions, and physiological signals can be used to recognize different emotions. Despite the discriminating properties to recognize emotions, the first three methods have been regarded as ineffective as the probability of human's voluntary and involuntary concealing the real emotions can not be ignored. Physiological signals, on the other hand, are capable of providing more objective, and reliable emotion recognition. Based on physiological signals, several methods have been introduced for emotion recognition, yet, predominantly such approaches are invasive involving the placement of on-body sensors. The efficacy and accuracy of these approaches are hindered by the sensor malfunctioning and erroneous data due to human limbs movement. This study presents a non-invasive approach where machine learning complements the impulse radio ultra-wideband (IR-UWB) signals for emotion recognition. First, the feasibility of using IR-UWB for emotion recognition is analyzed followed by determining the state of emotions into happiness, disgust, and fear. These emotions are triggered using carefully selected video clips to human subjects involving both males and females. The convincing evidence that different breathing patterns are linked with different emotions has been leveraged to discriminate between different emotions. Chest movement of thirty-five subjects is obtained using IR-UWB radar while watching the video clips in solitude. Extensive signal processing is applied to the obtained chest movement signals to estimate respiration rate per minute (RPM). The RPM estimated by the algorithm is validated by repeated measurements by a commercially available Pulse Oximeter. A dataset is maintained comprising gender, RPM, age, and associated emotions which are further used with several machine learning algorithms for automatic recognition of human emotions. Experiments reveal that IR-UWB possesses the potential to differentiate between different human emotions with a decent accuracy of 76% without placing any on-body sensors. Separate analysis for male and female participants reveals that males experience high arousal for happiness while females experience intense fear emotions. For disgust emotion, no large difference is found for male and female participants. To the best of the authors' knowledge, this study presents the first non-invasive approach using the IR-UWB radar for emotion recognition.

Microwave breast tumor localization using wavelet feature extraction and genetic algorithm-neural network.

PURPOSE: Ultra-Wide Band (UWB) microwave breast cancer detection is a promising new technology for routine physical examination and home monitoring. The existing microwave imaging algorithms for breast tumor detection are complex and the effect is still not ideal, due to the heterogeneity of breast tissue, skin reflection, and fibroglandular tissue reflection in backscatter signals. This study aims to develop a machine learning method to accurately locate breast tumor. METHODS: A microwave-based breast tumor localization method is proposed by time-frequency feature extraction and neural network technology. First, the received microwave array signals are converted into representative and compact features by 4-level Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA). Then, the Genetic Algorithm-Neural Network (GA-NN) is developed to tune hyper-parameters of the neural network adaptively. The neural network embedded in the GA-NN algorithm is a four-layer architecture and 10-fold cross-validation is performed. Through the trained neural network, the tumor localization performance is evaluated on four datasets that are created by FDTD simulation method from 2-D MRI-derived breast models with varying tissue density, shape, and size. Each dataset consists of 1000 backscatter signals with different tumor positions, in which the ratio of training set to test set is 9:1. In order to verify the generalizability and scalability of the proposed method, the tumor localization performance is also tested on a 3-D breast model. RESULTS: For these 2-D breast models with unknown tumor locations, the evaluation results show that the proposed method has small location errors, which are 0.6076 mm, 3.0813 mm, 2.0798 mm, and 3.2988 mm, respectively, and high accuracy, which is 99%, 80%, 94%, and 85%, respectively. Furthermore, the location error and the prediction accuracy of the 3-D breast model are 3.3896 mm and 81%. CONCLUSIONS: These evaluation results demonstrate that the proposed machine learning method is effective and accurate for microwave breast tumor localization. The traditional microwave-based breast cancer detection method is to reconstruct the entire breast image to highlight the tumor. Compared with the traditional method, our proposed method can directly get the breast tumor location by applying neural network to the received microwave array signals, and circumvent any complicated image reconstruction processing.

Frequency Band Characteristics of a Triboelectric Nanogenerator and Ultra-Wide-Band Vibrational Energy Harvesting.

Micromechanical vibration, as one of the most prevalent forms of energy in an ambient environment, has surpassing application potentials as the power source for self-powered electronics. A triboelectric nanogenerator (TENG) can effectively convert vibrational energy to electricity, which has the unique benefit of a wide-band over a traditional vibration energy harvester due to the contact electrification mechanism. Herein, the frequency band characteristics of vibrational TENG (V-TENG) were systematically elaborated. The mechanical model of V-TENG was established to explore its working mechanism for wide-band vibrational energy harvesting. By simulation analysis and experimental validation, the bandwidth dependence of V-TENG on acceleration magnitude, proof mass, stiffness, and gap distance was investigated in detail. With optimized structural parameters, an ultra-wide-band vibration energy harvester (UVEH) was developed by a tandem spring-mass structure. Within the ultra-wide-band range from 3 to 45 Hz, the UVEH can invariably illuminate 36 serial light-emitting diodes (LEDs) and charge a 33 µF capacitor to 1.5 V within 35 s. This work has quantitatively studied frequency band characteristics of V-TENG and provided a promising strategy for wide-band vibrational energy harvesting from a machine, bridge, water wave, and human motion.

Multi-UAV Area Coverage Based on Relative Localization: Algorithms and Optimal UAV Placement.

This paper is concerned with relative localization-based optimal area coverage placement using multiple unmanned aerial vehicles (UAVs). It is assumed that only one of the UAVs has its global position information before performing the area coverage task and that ranging measurements can be obtained among the UAVs by using ultra-wide band (UWB) sensors. In this case, multi-UAV relative localization and cooperative coverage control have to be run simultaneously, which is a quite challenging task. In this paper, we propose a single-landmark-based relative localization algorithm, combined with a distributed coverage control law. At the same time, the optimal multi-UAV placement problem was formulated as a quadratic programming problem by compromising between optimal relative localization and optimal coverage control and was solved by using Sequential Quadratic Programming (SQP) algorithms. Simulation results show that our proposed method can guarantee that a team of UAVs can efficiently localize themselves in a cooperative manner and, at the same time, complete the area coverage task.

Lab-Based Evaluation of Device-Free Passive Localization Using Multipath Channel Information.

The interconnection of devices, driven by the Internet of Things (IoT), enables a broad variety of smart applications and location-based services. The latter is often realized via transponder based approaches, which actively determine device positions within Wireless Sensor Networks (WSN). In addition, interpreting wireless signal measurements also enables the utilization of radar-like passive localization of objects, further enhancing the capabilities of WSN ranging from environmental mapping to multipath detection. For these approaches, the target objects are not required to hold any device nor to actively participate in the localization process. Instead, the signal delays caused by reflections at objects within the propagation environment are used to localize the object. In this work, we used Ultra-Wide Band (UWB) sensors to measure Channel Impulse Responses (CIRs) within a WSN. Determining an object position based on the CIR can be achieved by formulating an elliptical model. Based on this relation, we propose a CIR environmental mapping (CIR-EM) method, which represents a heatmap generation of the propagation environment based on the CIRs taken from radio communication signals. Along with providing imaging capabilities, this method also allows a more robust localization when compared to state-of-the-art methods. This paper provides a proof-of-concept of passive localization solely based on evaluating radio communication signals by conducting measurement campaigns in an anechoic chamber as a best-case environment. Furthermore, shortcomings due to physical layer limitations when using non-dedicated hardware and signals are investigated. Overall, this work lays a foundation for related research and further evaluation in more application-oriented scenarios.

Realizing UWB Antenna Array with Dual and Wide Rejection Bands Using Metamaterial and Electromagnetic Bandgaps Techniques.

This research article describes a technique for realizing wideband dual notched functionality in an ultra-wideband (UWB) antenna array based on metamaterial and electromagnetic bandgap (EBG) techniques. For comparison purposes, a reference antenna array was initially designed comprising hexagonal patches that are interconnected to each other. The array was fabricated on standard FR-4 substrate with thickness of 0.8 mm. The reference antenna exhibited an average gain of 1.5 dBi across 5.25-10.1 GHz. To improve the array's impedance bandwidth for application in UWB systems metamaterial (MTM) characteristics were applied it. This involved embedding hexagonal slots in patch and shorting the patch to the ground-plane with metallic via. This essentially transformed the antenna to a composite right/left-handed structure that behaved like series left-handed capacitance and shunt left-handed inductance. The proposed MTM antenna array now operated over a much wider frequency range (2-12 GHz) with average gain of 5 dBi. Notched band functionality was incorporated in the proposed array to eliminate unwanted interference signals from other wireless communications systems that coexist inside the UWB spectrum. This was achieved by introducing electromagnetic bandgap in the array by etching circular slots on the ground-plane that are aligned underneath each patch and interconnecting microstrip-line in the array. The proposed techniques had no effect on the dimensions of the antenna array (20 mm × 20 mm × 0.87 mm). The results presented confirm dual-band rejection at the wireless local area network (WLAN) band (5.15-5.825 GHz) and X-band satellite downlink communication band (7.10-7.76 GHz). Compared to other dual notched band designs previously published the footprint of the proposed technique is smaller and its rejection notches completely cover the bandwidth of interfering signals.

A Survey of Autonomous Vehicles: Enabling Communication Technologies and Challenges.

The Department of Transport in the United Kingdom recorded 25,080 motor vehicle fatalities in 2019. This situation stresses the need for an intelligent transport system (ITS) that improves road safety and security by avoiding human errors with the use of autonomous vehicles (AVs). Therefore, this survey discusses the current development of two main components of an ITS: (1) gathering of AVs surrounding data using sensors; and (2) enabling vehicular communication technologies. First, the paper discusses various sensors and their role in AVs. Then, various communication technologies for AVs to facilitate vehicle to everything (V2X) communication are discussed. Based on the transmission range, these technologies are grouped into three main categories: long-range, medium-range and short-range. The short-range group presents the development of Bluetooth, ZigBee and ultra-wide band communication for AVs. The medium-range examines the properties of dedicated short-range communications (DSRC). Finally, the long-range group presents the cellular-vehicle to everything (C-V2X) and 5G-new radio (5G-NR). An important characteristic which differentiates each category and its suitable application is latency. This research presents a comprehensive study of AV technologies and identifies the main advantages, disadvantages, and challenges.

Measurement of pulse transit time using ultra-wideband radar.

BACKGROUND: The pulse transit time is an important factor that can be used to estimate the blood pressure indirectly. In many studies, pressures in the artery near and far from the heart are measured or the electrocardiogram and photoplethysmography are used to calculate the pulse transit time. In other words, the so-called contact measurements have been mainly used in these studies. OBJECTIVE: In this paper, a new method based on radar technology to measure the pulse transit time in a non-contact manner is proposed. METHODS: Radar pulses were simultaneously emitted to the chest and the wrist, and the reflected pulses were accumulated. Heartbeats were extracted by performing principal component analysis on each time series belonging to the accumulated pulses. Then, the matched heartbeat pairs were found among the heartbeats obtained from the chest and wrist and the time delay between them, i.e. the pulse transit time, was obtained. RESULTS: By comparing the pulse transit times obtained by the proposed method with those obtained by conventional methods, it is confirmed that the proposed method using the radar can be used to obtain the pulse transit time in a non-contact manner.