Devendra K. Misra
Other affiliations: University of Wisconsin-Madison
Bio: Devendra K. Misra is an academic researcher from University of Wisconsin–Milwaukee. The author has contributed to research in topics: Permittivity & Admittance. The author has an hindex of 9, co-authored 24 publications receiving 915 citations. Previous affiliations of Devendra K. Misra include University of Wisconsin-Madison.
TL;DR: An X-band microwave life-detection system has been developed for detecting the heartbeat and breathing of human subjects lying on the ground at a distance of about 30 m or located behind a cinder block wall.
Abstract: An X-band microwave life-detection system has been developed for detecting the heartbeat and breathing of human subjects lying on the ground at a distance of about 30 m or located behind a cinder block wall. The basic principle of the system is to illuminate the subject with a low-intensity microwave beam, and then from the back-scattered microwave signal, extract the heart and breathing signals that modulate it. The circuit description of the system and some experimental results are presented. Potential applications of the system are noted.
01 Sep 2004
TL;DR: In this article, the authors propose a distributed circuit analysis of transmission lines and propose a method for converting them to signal-flow graphs, which are then used to represent the signal flow graph of a single-port device.
Abstract: 1 Introduction. 1.1 Microwave Transmission Lines. 1.2 Transmitter and Receiver Architectures. 2 Communication Systems. 2.1 Terrestrial Communication. 2.2 Satellite Communication. 2.3 Radio-Frequency Wireless Services. 2.4 Antenna Systems. 2.5 Noise and Distortion. Suggested Reading. Problems. 3 Transmission Lines. 3.1 Distributed Circuit Analysis of Transmission Lines. 3.2 Sending-End Impedance. 3.3 Standing Wave and Standing Wave Ratio. 3.4 Smith Chart. Suggested Reading. Problems. 4 Electromagnetic Fields and Waves. 4.1 Fundamental Laws of Electromagnetic Fields. 4.2 The Wave Equation and Uniform Plane Wave Solutions. 4.3 Boundary Conditions. 4.4 Uniform Plane Wave Incident Normally on an Interface. 4.5 Modified Maxwell's Equations and Potential Functions. 4.6 Construction of Solutions. 4.7 Metallic Parallel-Plate Waveguide. 4.8 Metallic Rectangular Waveguide. 4.9 Metallic Circular Waveguide. Suggested Reading. Problems. 5 Resonant Circuits. 5.1 Series Resonant Circuits. 5.2 Parallel Resonant Circuits. 5.3 Transformer-Coupled Circuits. 5.4 Transmission Line Resonant Circuits. 5.5 Microwave Resonators. Suggested Reading. Problems. 6 Impedance-Matching Networks. 6.1 Single Reactive Element or Stub Matching Networks. 6.2 Double-Stub Matching Networks. 6.3 Matching Networks Using Lumped Elements. Suggested Reading. Problems. 7 Impedance Transformers. 7.1 Single-Section Quarter-Wave Transformers. 7.2 Multisection Quarter-Wave Transformers. 7.3 Transformer with Uniformly Distributed Section Reflection Coefficients. 7.4 Binomial Transformers. 7.5 Chebyshev Transformers. 7.6 Exact Formulation and Design of Multisection Impedance Transformers. 7.7 Tapered Transmission Lines. 7.8 Synthesis of Transmission Line Tapers. 7.9 Bode-Fano Constraints for Lossless Matching Networks. Suggested Reading. Problems. 8 Two-Port Networks. 8.1 Impedance Parameters. 8.2 Admittance Parameters. 8.3 Hybrid Parameters. 8.4 Transmission Parameters. 8.5 Conversion of Impedance, Admittance, Chain, and Hybrid Parameters. 8.6 Scattering Parameters. 8.7 Conversion From Impedance, Admittance, Chain, and Hybrid Parameters to Scattering Parameters, or Vice Versa. 8.8 Chain Scattering Parameters. Suggested Reading. Problems. 9 Filter Design. 9.1 Image Parameter Method. 9.2 Insertion-Loss Method. 9.3 Microwave Filters. Suggested Reading. Problems. 10 Signal-Flow Graphs and Their Applications. 10.1 Definitions and Manipulation of Signal-Flow Graphs. 10.2 Signal-Flow Graph Representation of a Voltage Source. 10.3 Signal-Flow Graph Representation of a Passive Single-Port Device. 10.4 Power Gain Equations. Suggested Reading. Problems. 11 Transistor Amplifier Design. 11.1 Stability Considerations. 11.2 Amplifier Design for Maximum Gain. 11.3 Constant-Gain Circles. 11.4 Constant Noise Figure Circles. 11.5 Broadband Amplifiers. 11.6 Small-Signal Equivalent-Circuit Models of Transistors. 11.7 DC Bias Circuits for Transistors. Suggested Reading. Problems. 12 Oscillator Design. 12.1 Feedback and Basic Concepts. 12.2 Crystal Oscillators. 12.3 Electronic Tuning of Oscillators. 12.4 Phase-Locked Loop. 12.5 Frequency Synthesizers. 12.6 One-Port Negative Resistance Oscillators. 12.7 Microwave Transistor Oscillators. Suggested Reading. Problems. 13 Detectors and Mixers. 13.1 Amplitude Modulation. 13.2 Frequency Modulation. 13.3 Switching-Type Mixers. 13.4 Conversion Loss. 13.5 Intermodulation Distortion in Diode-Ring Mixers. 13.6 FET Mixers. Suggested Reading. Problems. Appendix 1: Decibels and Neper. Appendix 2" Characteristics of Selected Transmission Lines. Appendix 3: Specifications of Selected Coaxial Lines and Waveguides. Appendix 4: Some Mathematical Formulas. Appendix 5: Vector Identities. Appendix 6: Some Useful Network Transformations. Appendix 7: Properties of Some Materials. Appendix 8: Common Abbreviations. Appendix 9: Physical Constants. Index.
•13 Feb 1991
TL;DR: In this paper, a method and apparatus for determining the permittivity of a sample is disclosed, which includes applying an AC electrical signal in the microwave frequency range via a coaxial probe having an end position near the sample and measuring the reflection coefficient of the sample.
Abstract: A method and apparatus for determining the permittivity of a sample is disclosed. The method includes applying an AC electrical signal in the microwave frequency range via a coaxial probe having an end position near the sample and measuring the reflection coefficient of the sample. The complex permittivity of the sample is determined from an admittance parameter of the sample/probe combination and a system constant. The system constant is determined by measuring the reflection coefficients of four standards having known complex permittivity. The admittance parameter of the sample/probe combination is determined from the admittance parameters of two standards/probe combinations and the measured reflection coefficients of the sample and the four standards. The admittance parameters of the two standard/probe combinations are determined from the known complex permittivities of the two standards and the system constant. The apparatus includes a coaxial probe having an end positioned near the sample, a microwave frequency generator and a device for measuring a reflection coefficient are connected to the other end of the coaxial probe. A microprocessor determines the complex permittivity of the sample from the measured reflection coefficients of the sample and four standards having known complex permittivities.
01 Mar 2001
TL;DR: This paper reviews recent advances in biomedical and healthcare applications of Doppler radar that remotely detects heartbeat and respiration of a human subject and reviews different architectures, baseband signal processing, and system implementations.
Abstract: 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.
TL;DR: The models and methods presented in this review are sufficiently general to be of use in a broad range of applications for biological dielectrophoresis and particle electrokinetics and may be extended further to the case of nonspherical particles, where alignment torques can be considered.
Abstract: This article presents a concise, unifying treatment of the electromechanics of small particles under the influence of electroquasistatic fields and offers a set of models useful in calculating electrical forces and torques on biological particles in the size range from /spl sim/1 to /spl sim/100 /spl mu/m. The theory is used to consider DEP trapping, electrorotation, traveling-wave induced motion, and orientational effects. The effective dipole method, and its generalization to effective multipoles, makes it possible to treat multilayered concentric shells and particles exhibiting ohmic and dielectric loss. This method may be extended further to the case of nonspherical particles, where alignment torques can be considered. These capabilities are well suited to modeling DEP behavior of biological particles including cells. The models and methods presented in this review are sufficiently general to be of use in a broad range of applications for biological dielectrophoresis and particle electrokinetics. The range of validity can be stated confidently to cover particles having diameters approximately 1/spl mu/m and larger.
TL;DR: Substantial improvements offered by the proposed phased-MIMO radar technique are demonstrated analytically and by simulations through analyzing the corresponding beam patterns and the achievable output signal-to-noise-plus-interference ratios.
Abstract: We propose a new technique for multiple-input multiple-output (MIMO) radar with colocated antennas which we call phased-MIMO radar. The new technique enjoys the advantages of the MIMO radar without sacrificing the main advantage of the phased-array radar which is the coherent processing gain at the transmitting side. The essence of the proposed technique is to partition the transmit array into a number of subarrays that are allowed to overlap. Then, each subarray is used to coherently transmit a waveform which is orthogonal to the waveforms transmitted by other subarrays. Coherent processing gain can be achieved by designing a weight vector for each subarray to form a beam towards a certain direction in space. Moreover, the subarrays are combined jointly to form a MIMO radar resulting in higher angular resolution capabilities. Substantial improvements offered by the proposed phased-MIMO radar technique as compared to the phased-array and MIMO radar techniques are demonstrated analytically and by simulations through analyzing the corresponding beam patterns and the achievable output signal-to-noise-plus-interference ratios. Both analytical and simulation results validate the effectiveness of the proposed phased-MIMO radar.
TL;DR: A new sensitive microwave life-detection system which can be used to locate human subjects buried earthquake rubble or hidden behind various barriers has been constructed and tested extensively.
Abstract: A new sensitive microwave life-detection which can be used to locate human subjects buried earthquake rubble or hidden behind various barriers has been constructed. This system operating at 1150 MHz or 450 MHz can detect the breathing and heartbeat signals of human subjects through an earthquake rubble or a construction barrier of about 10-ft thickness. The basic physical principle for the operation of a microwave life-detection system is rather simple. When a microwave beam of appropriate frequency (L or S band) is aimed at a pile of earthquake rubble covering a human subject or illuminated through a barrier obstructing a human subject, the microwave beam can penetrate the rubble or the barrier to reach the human subject. When the human subject is illuminated by a microwave beam, the reflected wave from the human subject will be modulated by tile subject's body movements, which include the breathing and the heartbeat. If the clutter consisting of the reflected wave from stationary background can be completely eliminated and the reflected wave from the human subject's body is properly modulated, the breathing and heartbeat signals of the subject can be extracted. Thus, a human subject buried under earthquake rubble or hidden behind barriers can be located. This system has been tested extensively in a simulated earthquake rubble in the laboratory and also in a field test using realistic earthquake rubble conducted by a Federal Emergency Management Agency (FEMA) Task Force.
••22 Jun 2015
TL;DR: The extensive experiments demonstrate that the system can accurately capture vital signs during sleep under realistic settings, and achieve comparable or even better performance comparing to traditional and existing approaches, which is a strong indication of providing non-invasive, continuous fine-grained vital signs monitoring without any additional cost.
Abstract: Tracking human vital signs of breathing and heart rates during sleep is important as it can help to assess the general physical health of a person and provide useful clues for diagnosing possible diseases. Traditional approaches (e.g., Polysomnography (PSG)) are limited to clinic usage. Recent radio frequency (RF) based approaches require specialized devices or dedicated wireless sensors and are only able to track breathing rate. In this work, we propose to track the vital signs of both breathing rate and heart rate during sleep by using off-the-shelf WiFi without any wearable or dedicated devices. Our system re-uses existing WiFi network and exploits the fine-grained channel information to capture the minute movements caused by breathing and heart beats. Our system thus has the potential to be widely deployed and perform continuous long-term monitoring. The developed algorithm makes use of the channel information in both time and frequency domain to estimate breathing and heart rates, and it works well when either individual or two persons are in bed. Our extensive experiments demonstrate that our system can accurately capture vital signs during sleep under realistic settings, and achieve comparable or even better performance comparing to traditional and existing approaches, which is a strong indication of providing non-invasive, continuous fine-grained vital signs monitoring without any additional cost.