Xiaomeng Gao

Data-Based Quadrature Imbalance Compensation for a CW Doppler Radar System

A method for quadrature imbalance compensation in direct-conversion quadrature Doppler radar systems, based on data obtained using a mechanical target and an ellipse fit method, is reported. The proposed method can be used with different architectures of Doppler radar and eliminates the need to modify the radar in order to perform imbalance measurements. A mechanical target was used to provide sufficient motion to create a significant segment of an ellipse in the in-phase/quadrature trace to obtain correction factors with high accuracy. Parametric simulations were performed to analyze the accuracy of this technique in the presence of varying noise and target displacements. This method is compared with an existing phase-shifter-based imbalance computation technique for the measurement of known displacements and is shown to give consistent and more accurate results. Experimental data, consistent with simulations, demonstrates that accurate correction is obtained with 65% of the ellipse, resulting in a displacement error of less than 6%.

E-healthcare: Remote monitoring, privacy, and security

E-healthcare refers to healthcare practice supported by the use of electronic devices and communication. As traditional internet transitions to Internet of Things, with objects and people interacting and sharing information, there are many opportunities to use that technology for improving healthcare outcomes while reducing cost. In this paper we discuss several potential applications of Internet of Things in e-healthcare, including remote monitoring for elderly and sleep disorders, and privacy and security issues associated with electronic medical records and data.

Quadrature Imbalance Compensation With Ellipse-Fitting Methods for Microwave Radar Physiological Sensing

Accurate displacement measurement using quadrature Doppler radar requires amplitudes and phase imbalance compensation. Previously, this imbalance calibration has required cumbersome hardware modifications and thus can only be performed in a laboratory setting. Recently, a data-based method that does not require hardware modifications has been proposed. This simplifies the calibration process and allows the calibration to be performed on-site periodically. The method is called ellipse fitting. In this paper, the different factors affecting imbalance estimation accuracy, namely, arc length, initial phase angle, and noise level were thoroughly investigated. The Levenberg-Marquardt (LM) algorithm is proposed for the first time to increase the estimation accuracy as compared to the previously suggested algebraic fitting. Comprehensive simulations and experimental data show that the algebraic fitting method results in biased estimates. The proposed LM method has also been demonstrated to be more robust to noise, varying arc lengths, and different initial angles. The LM method reaches sufficient imbalance estimation accuracy with an arc length of 40% and a noise level of 1.5%.

Non-contact displacement estimation using Doppler radar

Non-contact Doppler radar has been used extensively for detection of physiological motion. Most of the results published to date have been focused on estimation of the physiological rates, such as respiratory rate and heart rate, with CW and modulated waveforms in various settings. Accurate assessment of chest displacement may take this type of monitoring to the new level, by enabling the estimation of associated cardiopulmonary volumes, and possibly pulse pressure. To obtain absolute chest displacement with highest precision, full nonlinear phase demodulation of the quadrature radar outputs must be performed. The accuracy of this type of demodulation is limited by the drifting received RF power, varying dc offset, and channel quadrature imbalance. In this paper we demonstrate that if relatively large motion is used to calibrate the system, smaller motion displacement may be acquired with the accuracy on the order of 30 μm.

Signal processing techniques for vital sign monitoring using mobile short range doppler radar

This paper investigates mobile noncontact vital sign monitoring device for short range application. The radar module is mounted on a programmable linear stage, and precise stage movements are monitored by an optical tracking system. The motion artifacts due to radar system movements are removed using IIR filter and adaptive noise cancellation techniques. The system is capable of extracting respiration rate even in the presence of radar module motion. In many applications, vital sign measurement from a mobile platform will be very useful, i.e., using unmanned vehicle as a first responder in battlefield including other military and medical applications. Our experiments and theoretical techniques provide a baseline that can be potentially used to measure vital signs from any arbitrarily moving radar system.

Considerations for integration of a physiological radar monitoring system with gold standard clinical sleep monitoring systems

A design for a physiological radar monitoring system (PRMS) that can be integrated with clinical sleep monitoring systems is presented. The PRMS uses two radar systems at 2.45GHz and 24 GHz to achieve both high sensitivity and high resolution. The system can acquire data, perform digital processing and output appropriate conventional analog outputs with a latency of 130 ms, which can be recorded and displayed by a gold standard sleep monitoring system, along with other standard sensor measurements.

Radius Correction Technique for Doppler Radar Noncontact Periodic Displacement Measurement

Noncontact physiological monitoring using Doppler radar has been studied extensively. Most commonly, continuous-wave (CW) quadrature Doppler radar is used to measure cardiopulmonary rates. Accurate displacement measurement can provide physiological waveform recovery, which may enable tidal volume and pulse pressure estimation. In this paper, we propose a calibration technique that enables high-accuracy millimeter-order periodic displacement measurements using CW quadrature Doppler radar. Theoretical analysis of center estimation error and its propagation effect are presented. Simulations are performed to show how noise and limited arc length affect error and affect the accuracy of center estimation, as well as improvements after calibration. A high-precision linear stage was employed to create periodic motion for evaluating the performance of calibration technique. Experimental results demonstrate that the proposed calibration technique enables displacement measurement with accuracy within tens of micrometers.

Small-scale displacement measurement with passive harmonic RF tag using Doppler radar

Measurement accuracy of the displacement from human cardiopulmonary activities has potential in predicting physiological information for the purpose of biomedical remote sensing and non-contact monitoring. In this paper, an RF frequency doubling tag was used for detecting small displacement with high accuracy. A heterodyne and a homodyne quadrature radar receiving systems were used to detect small scale tag motion and non-tagged motion from a distance, respectively. Arctangent demodulation algorithm and imbalance compensation technique were applied to the raw radar data for displacement estimation. Simulation and experimental results were compared, indicating that by using the frequency doubling tag, a better accuracy can be achieved for small displacement estimation with Doppler radar.

Wrist-worn heartbeat monitoring system based on bio-impedance analysis

In this paper, a bio-impedance analysis (BIA) based wrist-worn heartbeat monitoring system is proposed. The system is able to estimate heart rate from a subjects wrist with only four electrodes. The design is achieved with a standard BIA device and off-the-shelf components for signal conditioning. The measured heartbeat-related impedance signal is compared with a reference heart rate signal obtained from piezoelectric finger pulse transducer. The BIA results agree with the reference, which validates the feasibility of the proposed system. To the best of our knowledge, this is the first reported BIA heartbeat monitoring system in the wristband configuration.

Barcode based hand gesture classification using AC coupled quadrature Doppler radar

This paper presents a novel method of using AC coupled quadrature Doppler radar for gesture classification. A barcode is generated based on time-domain zero-crossing characteristics of quadrature components in reflected signals of hand gesture. Each motion is repeated within 60 seconds to create a distinguishable pattern on a barcode plot, which can be used for differentiation of motion types and gesture classification.