376 research outputs found

    Millimeter and sub-millimeter wave radiometers for atmospheric remote sensing from CubeSat platforms

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    2018 Fall.Includes bibliographical references.To view the abstract, please see the full text of the document

    DESIGN OF LOW-POWER LOW-VOLTAGE SUCCESSIVE-APPROXIMATION ANALOG-TO-DIGITAL CONVERTERS

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    Ph.DDOCTOR OF PHILOSOPH

    High-Speed Low-Power Analog to Digital Converter for Digital Beam Forming Systems

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    abstract: Time-interleaved analog to digital converters (ADCs) have become critical components in high-speed communication systems. Consumers demands for smaller size, more bandwidth and more features from their communication systems have driven the market to use modern complementary metal-oxide-semiconductor (CMOS) technologies with shorter channel-length transistors and hence a more compact design. Downscaling the supply voltage which is required in submicron technologies benefits digital circuits in terms of power and area. Designing accurate analog circuits, however becomes more challenging due to the less headroom. One way to overcome this problem is to use calibration to compensate for the loss of accuracy in analog circuits. Time-interleaving increases the effective data conversion rate in ADCs while keeping the circuit requirements the same. However, this technique needs special considerations as other design issues associated with using parallel identical channels emerge. The first and the most important is the practical issue of timing mismatch between channels, also called sample-time error, which can directly affect the performance of the ADC. Many techniques have been developed to tackle this issue both in analog and digital domains. Most of these techniques have high complexities especially when the number of channels exceeds 2 and some of them are only valid when input signal is a single tone sinusoidal which limits the application. This dissertation proposes a sample-time error calibration technique which bests the previous techniques in terms of simplicity, and also could be used with arbitrary input signals. A 12-bit 650 MSPS pipeline ADC with 1.5 GHz analog bandwidth for digital beam forming systems is designed in IBM 8HP BiCMOS 130 nm technology. A front-end sample-and-hold amplifier (SHA) was also designed to compare with an SHA-less design in terms of performance, power and area. Simulation results show that the proposed technique is able to improve the SNDR by 20 dB for a mismatch of 50% of the sampling period and up to 29 dB at 37% of the Nyquist frequency. The designed ADC consumes 122 mW in each channel and the clock generation circuit consumes 142 mW. The ADC achieves 68.4 dB SNDR for an input of 61 MHz.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

    Integrated Circuits and Systems for Smart Sensory Applications

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    Connected intelligent sensing reshapes our society by empowering people with increasing new ways of mutual interactions. As integration technologies keep their scaling roadmap, the horizon of sensory applications is rapidly widening, thanks to myriad light-weight low-power or, in same cases even self-powered, smart devices with high-connectivity capabilities. CMOS integrated circuits technology is the best candidate to supply the required smartness and to pioneer these emerging sensory systems. As a result, new challenges are arising around the design of these integrated circuits and systems for sensory applications in terms of low-power edge computing, power management strategies, low-range wireless communications, integration with sensing devices. In this Special Issue recent advances in application-specific integrated circuits (ASIC) and systems for smart sensory applications in the following five emerging topics: (I) dedicated short-range communications transceivers; (II) digital smart sensors, (III) implantable neural interfaces, (IV) Power Management Strategies in wireless sensor nodes and (V) neuromorphic hardware

    Analog and mixed-signal design and test techniques for improved reliability

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    The relentless evolution of semiconductor technology has led to a pervasive reliance on integrated circuits (ICs) across an array of applications, from consumer electronics to safety-critical systems in automotive and medical devices. Ensuring the reliability and robustness of these ICs has become paramount. This dissertation addresses the growing need for defect-oriented testing in analog and mixed-signal (AMS) circuits, introducing a novel digital-like methodology. It emphasizes breaking down complex AMS circuits into smaller, manageable subcircuits, which are rigorously examined using purely digital monitors and injectors. The methodology is resource-efficient, optimizing existing circuit resources to minimize area overhead and power consumption. A significant achievement lies in the development of a Built-In Self-Test (BIST) for a 12-bit Successive Approximation Register (SAR) Analog-to-Digital Converter (ADC), showcasing the approach's effectiveness and flexibility. Additionally, this dissertation pioneers a smart sensor design approach that reduces dependence on intricate device models, thereby ensuring high performance across a broad range of operating conditions. A case study on a temperature-to-digital converter (TDC) design demonstrates its capability to function reliably over an extensive temperature range. The methodology optimizes parameters, allowing energy-efficient sensor designs that meet industry standards while minimizing silicon area and power consumption. These works signify a dedicated commitment to advancing the reliability and functional safety of analog and mixed-signal circuits, contributing to the evolving landscape of IC design

    Built-in self-test and self-calibration for analog and mixed signal circuits

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    Analog-to-digital converters (ADC) are one of the most important components in modern electronic systems. In the mission-critical applications such as automotive, the reliability of the ADC is critical as the ADC impacts the system level performance. Due to the aging effect and environmental changes, the performance of the ADC may degrade and even fail to meet the accuracy requirement over time. Built-in self-test (BIST) and self-calibration are becoming the ultimate solution to achieve lifetime reliability. This dissertation introduces two ADC testing algorithms and two ADC built-in self-test circuit implementations to test the ADC integral nonlinearity (INL) and differential nonlinearity (DNL) on-chip. In the first testing algorithm, the ultrafast stimulus error removal and segmented model identification of linearity errors (USER-SMILE) is developed for ADC built-in self-test, which eliminates the need for precision stimulus and reduces the overall test time. In this algorithm, the ADC is tested twice with a nonlinear ramp, instead of using a linear ramp signal. Therefore, the stimulus can be easily generated on-chip in a low-cost way. For the two ramps, there is a constant voltage shift in between. As the input stimulus linearity is completely relaxed, there is no requirement on the waveform of the input stimulus as long as it covers the ADC input range. In the meantime, the high-resolution ADC linearity is modeled with segmented parameters, which reduces the number of samples required for achieving high-precision test, thus saving the test time. As a result, the USER-SMILE algorithm is able to use less than 1 sample/code nonlinear stimulus to test high resolution ADCs with less than 0.5 least significant bit (LSB) INL estimation error, achieving more than 10-time test time reduction. This algorithm is validated with both board-level implementation and on-chip silicon implementation. The second testing algorithm is proposed to test the INL/DNL for multi-bit-per-stages pipelined ADCs with reduced test time and better test coverage. Due to the redundancy characteristics of multi-bit-per-stages pipelined ADC, the conventional histogram test cannot estimate and calibrate the static linearity accurately. The proposed method models the pipelined ADC nonlinearity as segmented parameters with inter-stage gain errors using the raw codes instead of the final output codes. During the test phase, a pure sine wave is sent to the ADC as the input and the model parameters are estimated from the output data with the system identification method. The modeled errors are then removed from the digital output codes during the calibration phase. A high-speed 12-bit pipelined ADC is tested and calibrated with the proposed method. With only 4000 samples, the 12-bit ADC is accurately tested and calibrated to achieve less than 1 LSB INL. The ADC effective number of bits (ENOB) is improved from 9.7 bits to 10.84 bits and the spurious-free dynamic range (SFDR) is improved by more than 20dB after calibration. In the first circuit implementation, a low-cost on-chip built-in self-test solution is developed using an R2R digital-to-analog converter (DAC) structure as the signal generator and the voltage shift generator for ADC linearity test. The proposed DAC is a subradix-2 R2R DAC with a constant voltage shift generation capability. The subradix-2 architecture avoids positive voltage gaps caused by mismatches, which relaxes the DAC matching requirements and reduces the design area. The R2R DAC based BIST circuit is fabricated in TSMC 40nm technology with a small area of 0.02mm^2. Measurement results show that the BIST circuit is capable of testing a 15-bit ADC INL accurately with less than 0.5 LSB INL estimation error. In the second circuit implementation, a complete SAR ADC built-in self-test solution using the USER-SMILE is developed and implemented in a 28nm automotive microcontroller. A low-cost 12-bit resistive DAC with less than 12-bit linearity is used as the signal generator to test and calibrate a SAR ADC with a target linearity of 12 bits. The voltage shift generation is created inside the ADC with capacitor switching. The entire algorithm processing unit for USER-SMILE algorithm is also implemented on chip. The final testing results are saved in the memory for further digital calibration. Both the total harmonic distortion (THD) and the SFDR are improved by 20dB after calibration, achieving -84.5dB and 86.5dB respectively. More than 700 parts are tested to verify the robustness of the BIST solution

    FMCW Signals for Radar Imaging and Channel Sounding

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    A linear / stepped frequency modulated continuous wave (FMCW) signal has for a long time been used in radar and channel sounding. A novel FMCW waveform known as “Gated FMCW” signal is proposed in this thesis for the suppression of strong undesired signals in microwave radar applications, such as: through-the-wall, ground penetrating, and medical imaging radar. In these applications the crosstalk signal between antennas and the reflections form the early interface (wall, ground surface, or skin respectively) are much stronger in magnitude compared to the backscattered signal from the target. Consequently, if not suppressed they overshadow the target’s return making detection a difficult task. Moreover, these strong unwanted reflections limit the radar’s dynamic range and might saturate or block the receiver causing the reflection from actual targets (especially targets with low radar cross section) to appear as noise. The effectiveness of the proposed waveform as a suppression technique was investigated in various radar scenarios, through numerical simulations and experiments. Comparisons of the radar images obtained for the radar system operating with the standard linear FMCW signal and with the proposed Gated FMCW waveform are also made. In addition to the radar work the application of FMCW signals to radio propagation measurements and channel characterisation in the 60 GHz and 2-6 GHz frequency bands in indoor and outdoor environments is described. The data are used to predict the bit error rate performance of the in-house built measurement based channel simulator and the results are compared with the theoretical multipath channel simulator available in Matlab
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