Doppler Radar Sensor Research Articles

Software Defined Doppler Radar as a Contactless Multipurpose Microwave Sensor for Vibrations Monitoring.

A vibration sensor based on the use of a Software-Defined Radio (SDR) platform is adopted in this work to provide a contactless and multipurpose solution for low-cost real-time vibrations monitoring. In order to test the vibration detection ability of the proposed non-contact method, a 1 GHz Doppler radar sensor is simulated and successfully assessed on targets at various distances, with various oscillation frequencies and amplitudes. Furthermore, an SDR Doppler platform is practically realized, and preliminary experimental validations on a device able to produce a harmonic motion are illustrated to prove the effectiveness of the proposed approach.

Wireless Hand Gesture Recognition Based on Continuous-Wave Doppler Radar Sensors

Short-range continuous-wave Doppler radar sensors have been mainly used for noncontact detection of various motions. In this paper, we investigate the feasibility to implement the function of a remote mouse, an input device of a computer, by recognizing human gestures based on a dual-channel Doppler radar sensor. Direct conversion architecture, symmetric subcarrier modulation, and bandpass sampling techniques are used to obtain a cost-effective solution. An arcsine algorithm and a motion imaging algorithm are proposed to linearly reconstruct the hand and finger motions in a 2-D plane from the demodulated Doppler phase shifts. Experimental results verified the effectiveness of the proposed architecture and algorithms. Different from the frequency-domain “micro-Doppler” approach, the proposed remote gesture recognition based on linear motion reconstruction is able to recognize definitive signatures for the corresponding motions, exhibiting promising potential in practical applications of human–computer interaction.

Short-Range Doppler-Radar Signatures from Industrial Wind Turbines: Theory, Simulations, and Measurements

Industrial wind turbines are large constructions that require in-field monitoring. In this paper, short-range Doppler radar signatures of wind turbines are both mathematically analyzed and practically verified through simulations and experiments. Two custom-designed radar prototypes that operate at the $C$ and $K$ bands, respectively, are employed in the acquisition campaign. The unique features of the radar signal—in particular, some observed energetic flashes in the time-Doppler map—appear as curved lines for specific acquisition scenarios and/or for nonstraight blades. Furthermore, it is demonstrated that the use of high-frequency radar systems is beneficial in terms of improved spectrogram resolution. Experimental results coming from a 50-m-height wind turbine and a curved-blade 12-m-height turbine are also discussed, in this paper, in the context of the provided theoretical and simulation frameworks. This paper paves the way for noncontact structural health monitoring of industrial-type wind turbines through portable low-cost Doppler radar sensors.

Sleep stage classification by non-contact vital signs indices using Doppler radar sensors.

Disturbed sleep has become more common in recent years. To improve the quality of sleep, undergoing sleep observation has gained interest as a means to resolve possible problems. In this paper, we evaluate a non-restrictive and non-contact method for classifying real-time sleep stages and report on its potential applications. The proposed system measures heart rate (HR), heart rate variability (HRV), body movements, and respiratory signals of a sleeping person using two 24-GHz microwave radars placed beneath the mattress. We introduce a method that dynamically selects the window width of the moving average filter to extract the pulse waves from the radar output signals. The Pearson correlation coefficient between two HR measurements derived from the radars overnight, and the reference polysomnography was the average of 88.3% and the correlation coefficient for HRV parameters was the average of 71.2%. For identifying wake and sleep periods, the body-movement index reached sensitivity of 76.0%, and a specificity of 77.0% with 10 participants. Low-frequency (LF) components of HRV and the LF/HF ratio had a high degree of contribution and differed significantly across the three sleep stages (REM, LIGHT, and DEEP; p <; 0.01). In contrast, high-frequency (HF) components of HRV were not significantly different across the three sleep stages (p > 0.05). We applied a canonical discriminant analysis to identify wake or sleep periods and to classify the three sleep stages with leave-one-out cross validation. Classification accuracy was 66.4% for simply identifying wake and sleep, 57.1% for three stages (wake, REM, and NREM) and 34% for four stages (wake, REM, LIGHT, and DEEP). This is a novel system for measuring HRs, HRV, body movements, and respiratory intervals and for measuring high sensitivity pulse waves using two radar signals. It simplifies measurement of sleep stages and may be employed at nursing care facilities or by the general public to improve sleep quality.

Small and Short-Range Radar Systems [Book Review

The initial pages of this book contain a series of color pictures. The average page contains multiple pictures or tables, compressing the text to a minimum and rendering the book pleasant to read. The first flip through the pages will captivate the readers and compel them to regard the short text under an interesting image, even though this may happen somewhere in the middle of the book on a completely random page. The author is maintaining a companion website where various demonstration videos related to the book chapters can be found, watched, enjoyed, and, in some cases, mimicked to help build one's own radar. Similarly, several MATLAB scripts are provided by the author on his website so that interested readers can try the radar processing algorithms and demonstrations outlined in the book. Following an introductory chapter on the general subject of radars, the book is divided into two main parts: Part I contains six chapters on short-range radar systems, and Part II is devoted to applications. Police Doppler radar and motion sensors, automotive radar, and through-wall radar are the applications covered in Part II.

Towards development of a mobile RF Doppler sensor for continuous heart rate variability and blood pressure monitoring.

The standard in noninvasive blood pressure (BP) measurement is an inflatable cuff device based on the oscillometric method, which poses several practical challenges for continuous BP monitoring. Here, we present a novel ultra-wide band RF Doppler radar sensor for next-generation mobile interface for the purpose of characterizing fluid flow speeds, and for ultimately measuring cuffless blood flow in the human wrist. The system takes advantage of the 7.1~10.5 GHz ultra-wide band signals which can reduce transceiver complexity and power consumption overhead. Moreover, results obtained from hardware development, antenna design and human wrist modeling, and subsequent phantom development are reported. Our comprehensive lab bench system setup with a peristaltic pump was capable of characterizing various speed flow components during a linear velocity sweep of 5~62 cm/s. The sensor holds potential for providing estimates of heart rate and blood pressure.

An automatic in-home fall detection system using Doppler radar signatures

One in three elders over the age of 65 falls each year in the United States. This paper describes a non-invasive fall detection system based on a Doppler radar sensor. The developed system has been tested in two environments: laboratory and real senior living apartments. While some laboratory resul ts appeared in our previous papers, the main novelty of this paper consists in the deployment of our fall detection system in six apartments from TigerPlace (a senior living facility in Columbia, Missouri). The fall detection results obtained in our laboratory were excellent, with the radar placed on the ceiling performing better than on the floor. The fall detection system was then evaluated using radar data collected over two weeks in six TigerPlace apartments. The fall detection system successfully detected all six natural senior falls in an apartment for the examined one week.

Basic feasibility of breathing and pulse detection with a continuous wave Doppler radar sensor

s / Resuscitation 96S (2015) 43–157 53 not better in comparison with other causes of CA. These data suggest that further efforts are needed to prevent intubation-related CA. http://dx.doi.org/10.1016/j.resuscitation.2015.09.122

Noncontact Respiration Monitoring During Sleep With Microwave Doppler Radar

This paper demonstrates the measurement of respiration waveform during sleep with a noncontact radar sensor. Instead of measuring only the respiration rate, the methods that allow monitoring the absolute respiration displacement were studied. Absolute respiration displacement can in theory be measured with a quadrature microwave Doppler radar sensor and using the nonlinear demodulation as the channel combining method. However, in this paper, relative respiration displacement measures were used as a reference. This is the first time that longer data sets have been analyzed successfully with the nonlinear demodulation method. This paper consists of whole-night recordings of three patients in an uncontrolled environment. The reference respiration data were obtained from a full polysomnography recorded simultaneously. The feasibility of the nonlinear demodulation in a real-life setting has been unclear. However, this paper shows that it is successful most of the time. The coverage of successfully demodulated radar data was $\sim 58$ %–78%. The use of the nonlinear demodulation is not possible in the following cases: 1) if the chest wall displacement is too small compared with the wavelength of the radar; 2) if the radar data do not form an arc-like shape in the $IQ$ -plot; or 3) if there are large movement artifacts present in the data. Both in academic literature and in commercial radar devices, the data are processed based on the presumption that it forms either an arc or a line in the $IQ$ -plot. Our measurements show that the presumption is not always valid.

Design and Implementation of a Microwave Motion Detector with Low Power Consumption

In this paper, we propose a design of microwave motion detector using X-band doppler radar sensor to minimize the power consumption. To minimize the power consumption and implement battery operated system, pulse input with 2 KHz, 4% duty cycle is exerted on the doppler radar sensor. In order to simplify the process of working with ATmega2560 microcontroller unit, Arduino compatible board is designed and implemented. Arduino is open source hardware and many library software is published as open source tools. Smartphone app is also proposed and designed as a real-time user interface of the motion detector. The SQLite database on the Android mobile operating system is used for recording raw data of motion detection for post-processing job, such as fast Fourier transform (FFT). Bluetooth interface module is implemented on the motion detection board as a wireless communication interface to the smartphone. The speed of human movement is identified by post-processing FFT.

Evaluation of a Doppler radar sensor system for vital signs detection and activity monitoring in a radio-frequency shielded room

This study presents an evaluation of an advanced Doppler radar-based method for detection of vital signs, presence, and activity of a human subject in a test room with radar-signal reflecting aluminum-coated surfaces. Ten test subjects lay in four positions, and they sat in two locations in the room, both breathing normally and holding their breath. The mean ratios of the pulse rates determined from the radar signal and electrocardiography and respiration reference signals were 110% (respiration) and 99% (heartbeat), and the mean occupied and empty room radar signal variance ratios were 608 (breathing) and 20 (breath-hold). In a one-subject activity monitoring test, walking, standing and lying activities could be well separated from the radar signal. The results are promising and the proposed system seems to have potential to be used in position-independent health and activity monitoring of, for example, elderly people in care homes or intoxicated people in police custody.

Doppler Radar Motion Sensor With CMOS Digital DC-Tuning VGA and Inverter-Based Sigma-Delta Modulator

In most of the traditional miniature Doppler radar systems, ac coupling is adopted between the radio frequency front-end and baseband amplifier to block the dc offset due to clutter reflection. However, ac coupling causes distortion to low frequency signals and loses the dc information, which represents slowly changing or stationary moment of the target. A dc-coupled radar sensor system using a variable gain amplifier (VGA) with software-configured digital tuning architecture is presented in this paper to realize dc tuning and dc offset calibration. Furthermore, to process the output signals from the VGA, a novel low-voltage low-power inverter-based second-order sigma-delta modulator has been developed. The frequency of mechanical motion can be detected from the spectrum of the presented modulator output digital bit stream without a decimation filter, which can significantly reduce the cost and the power consumption. Furthermore, it can potentially detect the motion amplitude using the relative strength of the harmonics in the spectrum of the output digital bit steam. Experiments show that the presented digital dc-tuning VGA can completely relieve the radar sensor from circuit saturation and the inverter-based sigma-delta modulator can perform under low voltage and low power to accurately detect the movement frequency of the target without a decimation filter. Both the presented VGA and modulator show great potential for integrating a Doppler radar sensor system into a low-power high-accuracy single chip in the future.

High Dynamic-Range Motion Imaging Based on Linearized Doppler Radar Sensor

Miniaturized Doppler radar sensor (DRS) for noncontact motion detection is a hot topic in the microwave community. Previously, small-scale physiological signals such as human respiration and heartbeat rates are the primary interest of study. In this paper, we propose a comprehensive approach that can be used to improve the demodulation linearity of microwave DRSs, such that detailed time-domain motion information ranging from micro-scale to large scale can be accurately reconstructed. Experiments show that based on a digital-IF receiver architecture, dynamic dc offset tracking, and the extended differentiate and cross-multiply arctangent algorithm, the displacement and velocity of both micrometer-scale vibration of a tuning fork and meter-scale human walking can be accurately recovered. Our work confirms that substantial time-domain motion information is carried by the signals backscattered from moving objects. Retrieval of such information using DRSs can be potentially used in a wide range of healthcare and biomedical applications, such as motion pattern recognition and bio-signal measurements.

An automatic fall detection framework using data fusion of Doppler radar and motion sensor network.

This paper describes the ongoing work of detecting falls in independent living senior apartments. We have developed a fall detection system with Doppler radar sensor and implemented ceiling radar in real senior apartments. However, the detection accuracy on real world data is affected by false alarms inherent in the real living environment, such as motions from visitors. To solve this issue, this paper proposes an improved framework by fusing the Doppler radar sensor result with a motion sensor network. As a result, performance is significantly improved after the data fusion by discarding the false alarms generated by visitors. The improvement of this new method is tested on one week of continuous data from an actual elderly person who frequently falls while living in her senior home.

BUILDING BLOCKS FOR A 24 GHZ PHASED-ARRAY FRONT-END IN CMOS TECHNOLOGY FOR SMART STREETLIGHTS

According to a recent European Union report, lighting represents a significant share of electricity costs and the goal of reducing lighting power consumption by 20% demands the coupling of light-emitting diode (LED) lights with smart sensors and communication networks. In this context, this paper proposes the integration of these three elements into a smart streetlight, incorporating a 24 GHz phased-array (Ph-A) front-end (FE). The main building blocks of this Ph-A FE integrated in a low cost 90 nm complementary metal-oxide-semiconductor (CMOS) technology are fully characterized. The selected FE’s architecture allows the implementation of transceivers as well as Doppler radar sensors functionalities. More specifically, the Ph-A technology is applied to a Doppler radar sensor in order to realize multi-lane road scanning and pedestrian detection. That way, the smart streetlight can become eco-friendly by turning on the LEDs only when necessary as well as to measure traffic parameters such as vehicle speed, type and direction. Intercommunication between the smart streetlights is based on a time-sharing mechanism that uses the same FE reconfigured as transceiver. Thanks to this functionality, the recorded traffic information can be relayed through adjacent streetlights to a control center, and control commands and warnings can be spread through the network. The system requirements are derived assuming a simplified model of the operating scenario with a typical inter-light distance of 50 m and line-of-sight between lights. The radar range is around 60 m, which allows for continuous coverage from one streetlight to the adjacent one. Meanwhile, a communication range of 140 m is derived as a fundamental requirement for reliable communication between streetlight sensors because it allows bypassing of one node in case of failure. For the developed building blocks — a low-noise amplifier, a variable-gain amplifier, a voltage-controlled oscillator and a vector modulation phase shifter — the design methodology is presented together with measurement results. The system power, consumption, noise figure and gain are estimated by means of a system analysis based on the measured data from the implemented blocks and the state of the art performances for the missing parts. It is shown that the requirements can be fulfilled with a total power consumption of around 375 mW in Doppler radar sensor mode and around 190 mW in transceiver mode. To the authors’ knowledge, this kind of integration is new and overcomes some limitations of the currently used solutions based on infrared sensors and low-throughput communications.

Noncontact Distance and Amplitude-Independent Vibration Measurement Based on an Extended DACM Algorithm

Utilizing microwave continuous-wave Doppler radars to wirelessly detect mechanical vibrations have been attracting more and more interests in recent years. In this paper, aiming to solve the null point and nonlinear issues in small-angle approximation-based Doppler radar sensors and eliminate the codomain restriction in the arctangent demodulation approach, we propose and investigate an extended differentiate and cross-multiply (DACM) algorithm. With an additional accumulator, the noise performance of the original DACM algorithm is improved. Moreover, the amplitude information of the vibration can be directly retrieved from accumulation without involving any distance-dependent issue. Experimental validations show that the proposed algorithm can fully recover the vibration patterns with the measured noncalibrated amplitude agreeing well with the known precalibrated data. Application examples of mechanical fault detection and human vital sign detection are demonstrated, showing a wide range of potential applications of this algorithm.

5.8GHz ISM 대역 평면안테나의 송수신분리도 개선

In this paper, microstrip antenna to enhance the isolation between transmitting port and receiving port under the proximity objects is proposed, and applied to the Doppler radar sensor working at 5.8GHz ISM band which detects vital signals of a human body. Two 3dB quadrature hybrids are placed around radiation patch to form a balanced structure between transmitting port and receiving port, such that it consistently provides enhanced Tx/Rx isolation and excellent return loss over nearby objects. It is theoretically analyzed and simulated to verify the validity of the proposed application. The fabricated antenna that is 2mm away from the human body, has more than 16 dB return loss and at least 30dB isolation over ISM frequency band of 5.8GHz.

Cancellation of Unwanted Doppler Radar Sensor Motion Using Empirical Mode Decomposition

The operation of microwave Doppler radar for sensing physiological motion signals is heavily compromised under sensor motion. To that end, we investigate the feasibility of applying empirical mode decomposition method in this context, and demonstrate its effectiveness in removing sensor motion artifacts. This method is shown to be effective in canceling unwanted sensor motion with precision sufficient to enable accurate heart rate extraction. Theoretical analysis and simulation results illustrate the potential of the proposed approach for a wide range of frequency separation and amplitude ratios of physiological signals and motion artifacts. Experimental results confirm that separation success is not very sensitive to amplitude ratio. A heart rate is extracted with RMSE within 1 beat per minute even in the presence of mechanical motion and order of magnitude larger in amplitude than that of the heart signal.

A Review on Recent Advances in Doppler Radar Sensors for Noncontact Healthcare Monitoring

This paper reviews recent advances in biomedical and healthcare applications of Doppler radar that remotely detects heartbeat and respiration of a human subject. In the last decade, new front-end architectures, baseband signal processing methods, and system-level integrations have been proposed by many researchers in this field to improve the detection accuracy and robustness. The advantages of noncontact detection have drawn interests in various applications, such as energy smart home, baby monitor, cardiopulmonary activity assessment, and tumor tracking. While many of the reported systems were bench-top prototypes for concept verification, several portable systems and integrated radar chips have been demonstrated. This paper reviews different architectures, baseband signal processing, and system implementations. Validations of this technology in a clinical environment will also be discussed.

1-D Microwave Imaging of Human Cardiac Motion: An Ab-Initio Investigation

This paper presents an experimental investigation that demonstrates the possibility of 1-D imaging of human cardiac motion using a microwave Doppler sensor. Compared with the previous works that primarily monitored human respiration and heartbeat rates, the reconstruction of cardiac motion in this work will provide more information for time-domain clinical diagnosis. To fully recover the motion information from the backscattered microwave signal, an instrument-based digital-IF Doppler radar sensor employing a dc-offset removal and an extended differentiate and cross-multiply algorithm was used. A series of experiments were performed to investigate the effectiveness of the cardiac imaging from different orientations of a subject. Analysis on the experimental results indicates that in addition to the respiration and heartbeat rates, a 1-D time-domain cardiac motion that fits well with the known physiological description can be obtained. Our work reveals that substantial cardiac activity information is carried by the Doppler shifts of the backscattered microwave reflected from a human chest. The information can be reconstructed by properly designed hardware and algorithms. The possibility of noncontact cardiac imaging would have a great potential in clinical diagnosis and treatment of human heart diseases.