42 research outputs found

    Polarization Imaging Sensors in Advanced Feature CMOS Technologies

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    The scaling of CMOS technology, as predicted by Moore\u27s law, has allowed for realization of high resolution imaging sensors and for the emergence of multi-mega-pixel imagers. Designing imaging sensors in advanced feature technologies poses many challenges especially since transistor models do not accurately portray their performance in these technologies. Furthermore, transistors fabricated in advanced feature technologies operate in a non-conventional mode known as velocity saturation. Traditionally, analog designers have been discouraged from designing circuits in this mode of operation due to the low gain properties in single transistor amplifiers. Nevertheless, velocity saturation will become even more prominent mode of operation as transistors continue to shrink and warrants careful design of circuits that can exploit this mode of operation. In this research endeavor, I have utilized velocity saturation mode of operation in order to realize low noise imaging sensors. These imaging sensors incorporate low noise analog circuits at the focal plane in order to improve the signal to noise ratio and are fabricated in 0.18 micron technology. Furthermore, I have explored nanofabrication techniques for realizing metallic nanowires acting as polarization filters. These nanoscopic metallic wires are deposited on the surface of the CMOS imaging sensor in order to add polarization sensitivity to the CMOS imaging sensor. This hybrid sensor will serve as a test bed for exploring the next generation of low noise and highly sensitive polarization imaging sensors

    Linear Current-Mode Active Pixel Sensor

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    A current mode CMOS active pixel sensor (APS) providing linear light-to-current conversion with inherently low fixed pattern noise (FPN) is presented. The pixel features adjustable-gain current output using a pMOS readout transistor in the linear region of operation. This paper discusses the pixel’s design and operation, and presents an analysis of the pixel’s temporal noise and FPN. Results for zero and first-order pixel mismatch are presented. The pixel was implemented in a both a 3.3 V 0.35 µm and a 1.8 V 0.18 µm CMOS process. The 0.35 µm process pixel had an uncorrected FPN of 1.4%/0.7% with/without column readout mismatch. The 0.18 µm process pixel had 0.4% FPN after delta-reset sampling (DRS). The pixel size in both processes was 10 X 10 µm2, with fill factors of 26% and 66%, respectively

    Interfacing of neuromorphic vision, auditory and olfactory sensors with digital neuromorphic circuits

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    The conventional Von Neumann architecture imposes strict constraints on the development of intelligent adaptive systems. The requirements of substantial computing power to process and analyse complex data make such an approach impractical to be used in implementing smart systems. Neuromorphic engineering has produced promising results in applications such as electronic sensing, networking architectures and complex data processing. This interdisciplinary field takes inspiration from neurobiological architecture and emulates these characteristics using analogue Very Large Scale Integration (VLSI). The unconventional approach of exploiting the non-linear current characteristics of transistors has aided in the development of low-power adaptive systems that can be implemented in intelligent systems. The neuromorphic approach is widely applied in electronic sensing, particularly in vision, auditory, tactile and olfactory sensors. While conventional sensors generate a huge amount of redundant output data, neuromorphic sensors implement the biological concept of spike-based output to generate sparse output data that corresponds to a certain sensing event. The operation principle applied in these sensors supports reduced power consumption with operating efficiency comparable to conventional sensors. Although neuromorphic sensors such as Dynamic Vision Sensor (DVS), Dynamic and Active pixel Vision Sensor (DAVIS) and AEREAR2 are steadily expanding their scope of application in real-world systems, the lack of spike-based data processing algorithms and complex interfacing methods restricts its applications in low-cost standalone autonomous systems. This research addresses the issue of interfacing between neuromorphic sensors and digital neuromorphic circuits. Current interfacing methods of these sensors are dependent on computers for output data processing. This approach restricts the portability of these sensors, limits their application in a standalone system and increases the overall cost of such systems. The proposed methodology simplifies the interfacing of these sensors with digital neuromorphic processors by utilizing AER communication protocols and neuromorphic hardware developed under the Convolution AER Vision Architecture for Real-time (CAVIAR) project. The proposed interface is simulated using a JAVA model that emulates a typical spikebased output of a neuromorphic sensor, in this case an olfactory sensor, and functions that process this data based on supervised learning. The successful implementation of this simulation suggests that the methodology is a practical solution and can be implemented in hardware. The JAVA simulation is compared to a similar model developed in Nengo, a standard large-scale neural simulation tool. The successful completion of this research contributes towards expanding the scope of application of neuromorphic sensors in standalone intelligent systems. The easy interfacing method proposed in this thesis promotes the portability of these sensors by eliminating the dependency on computers for output data processing. The inclusion of neuromorphic Field Programmable Gate Array (FPGA) board allows reconfiguration and deployment of learning algorithms to implement adaptable systems. These low-power systems can be widely applied in biosecurity and environmental monitoring. With this thesis, we suggest directions for future research in neuromorphic standalone systems based on neuromorphic olfaction

    Photon Quantum Noise Limited Pixel and Array architectures in a-Si Technology for Large Area Digital Imaging Applications

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    A Voltage Controlled Oscillator (VCO) based pixel and array architecture is reported using amorphous silicon (a-Si) technology for large area digital imaging applications. The objectives of this research are to (a) demonstrate photon quantum noise limited pixel operation of less than 30 input referred noise electrons, (b) theoretically explore the use of the proposed VCO pixel architecture for photon quantum noise limited large area imaging applications, more specifically protein crystallography using a-Si, (c) to implement and demonstrate experimentally a quantum noise limited (VCO) pixel, a small prototype of quantum noise limited (VCO) pixelated array and a quantum noise limited (VCO) pixel integrated with direct detection selenium for energies compatible with a protein crystallography application. Electronic noise (phase noise) and metastability performance of VCO pixels in low cost, widely available a-Si technology will be theoretically calculated and measured for the first time in this research. The application of a VCO pixel architecture in thin film technologies to large area imaging modalities will be examined and a small prototype a-Si array integrated with an overlying selenium X-ray converter will be demonstrated for the first time. A-Si and poly-Si transistor technologies are traditionally considered inferior in performance to crystalline silicon, the dominant semiconductor technology today. This work v aims to extend the reach of low cost, thin film transistor a-Si technology to high performance analog applications (i.e. very low input referred noise) previously considered only the domain of crystalline silicon type semiconductor. The proposed VCO pixel architecture can enable large area arrays with quantum noise limited pixels using low cost thin film transistor technologies

    Bolometers

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    Infrared Detectors and technologies are very important for a wide range of applications, not only for Military but also for various civilian applications. Comparatively fast bolometers can provide large quantities of low cost devices opening up a new era in infrared technologies. This book deals with various aspects of bolometer developments. It covers bolometer material aspects, different types of bolometers, performance limitations, applications and future trends. The chapters in this book will be useful for senior researchers as well as beginning graduate students

    NASA SBIR abstracts of 1991 phase 1 projects

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    The objectives of 301 projects placed under contract by the Small Business Innovation Research (SBIR) program of the National Aeronautics and Space Administration (NASA) are described. These projects were selected competitively from among proposals submitted to NASA in response to the 1991 SBIR Program Solicitation. The basic document consists of edited, non-proprietary abstracts of the winning proposals submitted by small businesses. The abstracts are presented under the 15 technical topics within which Phase 1 proposals were solicited. Each project was assigned a sequential identifying number from 001 to 301, in order of its appearance in the body of the report. Appendixes to provide additional information about the SBIR program and permit cross-reference of the 1991 Phase 1 projects by company name, location by state, principal investigator, NASA Field Center responsible for management of each project, and NASA contract number are included

    Particle Physics Reference Library

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    This second open access volume of the handbook series deals with detectors, large experimental facilities and data handling, both for accelerator and non-accelerator based experiments. It also covers applications in medicine and life sciences. A joint CERN-Springer initiative, the “Particle Physics Reference Library” provides revised and updated contributions based on previously published material in the well-known Landolt-Boernstein series on particle physics, accelerators and detectors (volumes 21A,B1,B2,C), which took stock of the field approximately one decade ago. Central to this new initiative is publication under full open access
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