Ehsan Yavari

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%.

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.

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.

System-on-Chip based Doppler radar occupancy sensor

System-on-Chip (SoC) based Doppler radar occupancy sensor is developed through non contact detection of respiratory signals. The radio was developed using off the shelf low power RF CC2530 SoC chip by Texas Instruments. In order to save power, the transmitter sends signal intermittently at 2.405 GHz. Reflected pulses are demodulated, and the baseband signals are processed to recover periodic motion. The system was tested both with mechanical target and a human subject. In both cases Doppler radar detected periodic motion closely matched the actual motion, and it has been shown that an SoC based system can be used for subject detection.

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.

A Low-IF Tag-Based Motion Compensation Technique for Mobile Doppler Radar Life Signs Monitoring

This paper presents low IF techniques for noninvasive detection of vital signs from a mobile short-range Doppler radar platform. Stationary continuous-wave Doppler radar has been used for displacement measurement and vital signs detection. However, on a mobile platform, measurements become challenging due to motion artifacts induced by the platform. In this work, a complete compensated single transceiver radar system for vital signs detection in the presence of platform movement is demonstrated. In earlier related work, motion of the radar module was determined using cameras installed on site. However, practical mobile monitoring applications would preclude the use of such stationary cameras. In this work, an RF tag and a low IF radar architecture with an adaptive noise cancellation technique is employed to extract desired vital signs motion information even in the presence of large platform motion.

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.

A low cost simple RF front end using time-domain multiplexing for direction of arrival estimation of physiological signals

Doppler radar has been used for vital signs monitoring. Multiple subject monitoring and direction of arrival estimation is possible by using multiple antennas and receivers. The homodyne receiver requires a quadrature demodulator for each antenna. The complexity of the system and the number of baseband channels will increase with the number of antennas. In this paper we propose time-domain multiplexing of the RF outputs of a four element antenna array and down-conversion using a single IQ demodulator. We de-multiplex the outputs in baseband and estimate the DOA for mechanical targets and a human subject breathing in front of the radar.

Channel Imbalance Effects and Compensation for Doppler Radar Physiological Measurements

Effects of quadrature channel imbalance on Doppler radar physiological measurements, and new compensation methods, are investigated in this paper. Parametric simulations and experiments were performed to investigate the effects of amplitude imbalance, phase imbalance, and initial phase on Doppler radar obtained pattern, displacement, and rate estimation. It is demonstrated that channel imbalance can introduce significant displacement error, and that error is sensitive to initial phase. Furthermore, it is shown that in-phase and quadrature mismatch can introduce error in heart rate estimation. Two methods to achieve accurate displacement estimation were proposed and demonstrated. Using several initial angle measurement points within quarter wavelength, displacement estimation with errors less than 1% was achieved without any imbalance correction. Alternatively, by combining data points at varying initial angle locations, imbalance factors are estimated with high accuracy. This technique provides another viable method of imbalance compensation without the need for hardware modification, or a target moving with a large displacement.