316 research outputs found

    High Speed Camera Chip

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    abstract: The market for high speed camera chips, or image sensors, has experienced rapid growth over the past decades owing to its broad application space in security, biomedical equipment, and mobile devices. CMOS (complementary metal-oxide-semiconductor) technology has significantly improved the performance of the high speed camera chip by enabling the monolithic integration of pixel circuits and on-chip analog-to-digital conversion. However, for low light intensity applications, many CMOS image sensors have a sub-optimum dynamic range, particularly in high speed operation. Thus the requirements for a sensor to have a high frame rate and high fill factor is attracting more attention. Another drawback for the high speed camera chip is its high power demands due to its high operating frequency. Therefore, a CMOS image sensor with high frame rate, high fill factor, high voltage range and low power is difficult to realize. This thesis presents the design of pixel circuit, the pixel array and column readout chain for a high speed camera chip. An integrated PN (positive-negative) junction photodiode and an accompanying ten transistor pixel circuit are implemented using a 0.18 ”m CMOS technology. Multiple methods are applied to minimize the subthreshold currents, which is critical for low light detection. A layout sharing technique is used to increase the fill factor to 64.63%. Four programmable gain amplifiers (PGAs) and 10-bit pipeline analog-to-digital converters (ADCs) are added to complete on-chip analog to digital conversion. The simulation results of extracted circuit indicate ENOB (effective number of bits) is greater than 8 bits with FoM (figures of merit) =0.789. The minimum detectable voltage level is determined to be 470ΌV based on noise analysis. The total power consumption of PGA and ADC is 8.2mW for each conversion. The whole camera chip reaches 10508 frames per second (fps) at full resolution with 3.1mm x 3.4mm area.Dissertation/ThesisMasters Thesis Electrical Engineering 201

    A Column-parallel Single-Slope ADC with Signal-Dependent Multiple Sampling Technique for CMOS Image Sensor

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    Department of Electrical EngineeringBoth Charge-Coupled Device (CCD) and Complementary Metal-Oxide Semiconductor (CMOS) image sensor have same starting point ??? they convert light photons into electrons. Recently, CMOS image sensor (CIS) has been developed significantly. CIS is much less expensive to manufacture than CCD sensor. Also, CIS has advantages over high speed, low noise and low power consumption. Therefore, such features can be used for many applications. In general, CIS has the number of incoming photons dependent noise characteristics. In the bright condition, photon shot noise is dominant in CIS compared with other noise sources. Photon shot noise cannot be reduced by circuit technique in single frame. However, CIS has high SNR in bright condition because the slope of the increase in signal is faster than the slope of increase in noise. But, in the dark condition, photon shot noise is not dominant in CIS. Random noises have dominance In CIS in the dark condition. These effects of noises can be reduced by circuit techniques. In the same way, Indirect Time-of-Flight (I-TOF) sensor has similar characteristics. When it measures long distance, its depth accuracy is reduced because of lack of incoming photons same as CIS in the dark condition. Therefore, same circuit technique can be used for pursuing beneficial effects on CIS and I- TOF sensor. To increase SNR in CIS, imposing gain in correlated double sampling stage as pre-amplifier. Therefore, it can increase SNR and reducing effects of readout random noises. However, it cannot increase gain highly as we want because of saturation problem and large power consumption. Therefore, it is not an advantageous method of low power systems. Otherwise, the multiple sampling technique had been proposed. It averages out all of the readout random noises by sampling several times [7]. Therefore, noise power is reduced in the inverse of sampling number and in voltage domain, noise rms value is reduced in the inverse of square root of sampling number. However, sampling several times increases readout time which is proportional to sampling number significantly. Therefore, to alleviate trade-offs coming from multiple sampling, several approaches is developed in the past. Typical examples are signal-dependent multiple sampling technique, pseudo multiple sampling technique and conditional multiple sampling technique. First, the pseudo multiple sampling technique decreases resolution of ADC for keeping conventional readout time [8]. Therefore, all of the pixels will be sampled several times, regardless of the value of those pixel values. Therefore, it has a limitation of effects of multiple sampling because of quantization noise due to large quantization step for achieving larger sampling number. Second, the signal dependent multiple sampling technique has been proposed [9]. It changes its 8sampling number according to pixel values. However, this concept can be achieved after operation of conventional readout. Therefore, it at least doubles readout time compared with conventional one. Finally, conditional multiple sampling technique has been proposed [10]. Similarly, the number of samplings is changed depending on the pixel value. However, it divides into two casesthe bright condition and the dark condition. Therefore, its boundary errors will be significant in output images. The proposed ADC can achieve conserving readout time with using multiple ramp generators. Also, it can change the sampling number according to pixel values gradually without sacrificing resolution of ADC [12]. It is composed with column-level digital logic for ramp selection and ripple local counter then size problem is not critical problem. Therefore, it can reduce boundary errors through the sample counter of the intermediate level. With this concept, adjusting the number of ramp generators, depending on the application, it can take the appropriate sampling number and reduces the power consumption consideration. Therefore, proposed ADC is new concept of signal-dependent multiple sampling technique with several ramp generators without sacrificing ramp resolution and readout time.clos

    Low Power Analog to Digital Converters in Advanced CMOS Technology Nodes

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    The dissertation presents system and circuit solutions to improve the power efficiency and address high-speed design issues of ADCs in advanced CMOS technologies. For image sensor applications, a high-performance digitizer prototype based on column-parallel single-slope ADC (SS-ADC) topology for readout of a back-illuminated 3D-stacked CMOS image sensor is presented. To address the high power consumption issue in high-speed digital counters, a passing window (PW) based hybrid counter topology is proposed. To address the high column FPN under bright illumination conditions, a double auto-zeroing (AZ) scheme is proposed. The proposed techniques are experimentally verified in a prototype chip designed and fabricated in the TSMC 40 nm low-power CMOS process. The PW technique saves 52.8% of power consumption in the hybrid digital counters. Dark/bright column fixed pattern noise (FPN) of 0.0024%/0.028% is achieved employing the proposed double AZ technique for digital correlated double sampling (CDS). A single-column digitizer consumes total power of 66.8ÎŒW and occupies an area of 5.4 ”m x 610 ”m. For mobile/wireless receiver applications, this dissertation presents a low-power wide-bandwidth multistage noise-shaping (MASH) continuous-time delta-sigma modulator (CT-ΔΣM) employing finite impulse response (FIR) digital-to-analog converters (DACs) and encoder-embedded loop-unrolling (EELU) quantizers. The proposed MASH 1-1-1 topology is a cascade of three single-loop first-order CT-ΔΣM stages, each of which consists of an active-RC integrator, a current-steering DAC, and an EELU quantizer. An FIR filter in the main 1.5-bit DAC improves the modulator’s jitter sensitivity performance. FIR’s effect on the noise transfer function (NTF) of the modulator is compensated in the digital domain thanks to the MASH topology. Instead of employing a conventional analog direct feedback path, a 1.5-bit EELU quantizer based on multiplexing comparator outputs is proposed; this approach is suitable for highspeed operation together with power and area benefits. Fabricated in a 40-nm low-power CMOS technology, the modulator’s prototype achieves a 67.3 dB of signal-to-noise and distortion ratio (SNDR), 68 dB of signal-to-noise ratio (SNR), and 68.2 dB of dynamic range (DR) within 50.5 MHz of bandwidth (BW), while consuming 19 mW of total power (P). The proposed modulator features 161.5 dB of figure-of-merit (FOM), defined as FOM = SNDR + 10 log10 (BW/P)

    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

    Ultra-low noise, high-frame rate readout design for a 3D-stacked CMOS image sensor

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    Due to the switch from CCD to CMOS technology, CMOS based image sensors have become smaller, cheaper, faster, and have recently outclassed CCDs in terms of image quality. Apart from the extensive set of applications requiring image sensors, the next technological breakthrough in imaging would be to consolidate and completely shift the conventional CMOS image sensor technology to the 3D-stacked technology. Stacking is recent and an innovative technology in the imaging field, allowing multiple silicon tiers with different functions to be stacked on top of each other. The technology allows for an extreme parallelism of the pixel readout circuitry. Furthermore, the readout is placed underneath the pixel array on a 3D-stacked image sensor, and the parallelism of the readout can remain constant at any spatial resolution of the sensors, allowing extreme low noise and a high-frame rate (design) at virtually any sensor array resolution. The objective of this work is the design of ultra-low noise readout circuits meant for 3D-stacked image sensors, structured with parallel readout circuitries. The readout circuit’s key requirements are low noise, speed, low-area (for higher parallelism), and low power. A CMOS imaging review is presented through a short historical background, followed by the description of the motivation, the research goals, and the work contributions. The fundamentals of CMOS image sensors are addressed, as a part of highlighting the typical image sensor features, the essential building blocks, types of operation, as well as their physical characteristics and their evaluation metrics. Following up on this, the document pays attention to the readout circuit’s noise theory and the column converters theory, to identify possible pitfalls to obtain sub-electron noise imagers. Lastly, the fabricated test CIS device performances are reported along with conjectures and conclusions, ending this thesis with the 3D-stacked subject issues and the future work. A part of the developed research work is located in the Appendices.Devido Ă  mudança da tecnologia CCD para CMOS, os sensores de imagem em CMOS tornam se mais pequenos, mais baratos, mais rĂĄpidos, e mais recentemente, ultrapassaram os sensores CCD no que respeita Ă  qualidade de imagem. Para alĂ©m do vasto conjunto de aplicaçÔes que requerem sensores de imagem, o prĂłximo salto tecnolĂłgico no ramo dos sensores de imagem Ă© o de mudar completamente da tecnologia de sensores de imagem CMOS convencional para a tecnologia “3D-stacked”. O empilhamento de chips Ă© relativamente recente e Ă© uma tecnologia inovadora no campo dos sensores de imagem, permitindo vĂĄrios planos de silĂ­cio com diferentes funçÔes poderem ser empilhados uns sobre os outros. Esta tecnologia permite portanto, um paralelismo extremo na leitura dos sinais vindos da matriz de pĂ­xeis. AlĂ©m disso, num sensor de imagem de planos de silĂ­cio empilhados, os circuitos de leitura estĂŁo posicionados debaixo da matriz de pĂ­xeis, sendo que dessa forma, o paralelismo pode manter-se constante para qualquer resolução espacial, permitindo assim atingir um extremo baixo ruĂ­do e um alto debito de imagens, virtualmente para qualquer resolução desejada. O objetivo deste trabalho Ă© o de desenhar circuitos de leitura de coluna de muito baixo ruĂ­do, planeados para serem empregues em sensores de imagem “3D-stacked” com estruturas altamente paralelizadas. Os requisitos chave para os circuitos de leitura sĂŁo de baixo ruĂ­do, rapidez e pouca ĂĄrea utilizada, de forma a obter-se o melhor rĂĄcio. Uma breve revisĂŁo histĂłrica dos sensores de imagem CMOS Ă© apresentada, seguida da motivação, dos objetivos e das contribuiçÔes feitas. Os fundamentos dos sensores de imagem CMOS sĂŁo tambĂ©m abordados para expor as suas caracterĂ­sticas, os blocos essenciais, os tipos de operação, assim como as suas caracterĂ­sticas fĂ­sicas e suas mĂ©tricas de avaliação. No seguimento disto, especial atenção Ă© dada Ă  teoria subjacente ao ruĂ­do inerente dos circuitos de leitura e dos conversores de coluna, servindo para identificar os possĂ­veis aspetos que dificultem atingir a tĂŁo desejada performance de muito baixo ruĂ­do. Por fim, os resultados experimentais do sensor desenvolvido sĂŁo apresentados junto com possĂ­veis conjeturas e respetivas conclusĂ”es, terminando o documento com o assunto de empilhamento vertical de camadas de silĂ­cio, junto com o possĂ­vel trabalho futuro

    ?????? ?????? ???????????? ?????? ???????????? ??????????????? ?????????????????? ??? ???????????????

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    Department of Electrical EngineeringA Sensor system is advanced along sensor technologies are developed. The performance improvement of sensor system can be expected by using the internet of things (IoT) communication technology and artificial neural network (ANN) for data processing and computation. Sensors or systems exchanged the data through this wireless connectivity, and various systems and applications are possible to implement by utilizing the advanced technologies. And the collected data is computed using by the ANN and the efficiency of system can be also improved. Gas monitoring system is widely need from the daily life to hazardous workplace. Harmful gas can cause a respiratory disease and some gas include cancer-causing component. Even though it may cause dangerous situation due to explosion. There are various kinds of hazardous gas and its characteristics that effect on human body are different each gas. The optimal design of gas monitoring system is necessary due to each gas has different criteria such as the permissible concentration and exposure time. Therefore, in this thesis, conventional sensor system configuration, operation, and limitation are described and gas monitoring system with wireless connectivity and neural network is proposed to improve the overall efficiency. As I already mentioned above, dangerous concentration and permissible exposure time are different depending on gas types. During the gas monitoring, gas concentration is lower than a permissible level in most of case. Thus, the gas monitoring is enough with low resolution for saving the power consumption in this situation. When detecting the gas, the high-resolution is required for the accurate concentration detecting. If the gas type is varied in the above situation, the amount of calculation increases exponentially. Therefore, in the conventional systems, target specifications are decided by the highest requirement in the whole situation, and it occurs increasing the cost and complexity of readout integrated circuit (ROIC) and system. In order to optimize the specification, the ANN and adaptive ROIC are utilized to compute the complex situation and huge data processing. Thus, gas monitoring system with learning-based algorithm is proposed to improve its efficiency. In order to optimize the operation depending on situation, dual-mode ROIC that monitoring mode and precision mode is implemented. If the present gas concentration is decided to safe, monitoring mode is operated with minimal detecting accuracy for saving the power consumption. The precision mode is switched when the high-resolution or hazardous situation are detected. The additional calibration circuits are necessary for the high-resolution implementation, and it has more power consumption and design complexity. A high-resolution Analog-to-digital converter (ADC) is kind of challenges to design with efficiency way. Therefore, in order to reduce the effective resolution of ADC and power consumption, zooming correlated double sampling (CDS) circuit and prediction successive approximation register (SAR) ADC are proposed for performance optimization into precision mode. A Microelectromechanical systems (MEMS) based gas sensor has high-integration and high sensitivity, but the calibration is needed to improve its low selectivity. Conventionally, principle component analysis (PCA) is used to classify the gas types, but this method has lower accuracy in some case and hard to verify in real-time. Alternatively, ANN is powerful algorithm to accurate sensing through collecting the data and training procedure and it can be verified the gas type and concentration in real-time. ROIC was fabricated in complementary metal-oxide-semiconductor (CMOS) 180-nm process and then the efficiency of the system with adaptive ROIC and ANN algorithm was experimentally verified into gas monitoring system prototype. Also, Bluetooth supports wireless connectivity to PC and mobile and pattern recognition and prediction code for SAR ADC is performed in MATLAB. Real-time gas information is monitored by Android-based application in smartphone. The dual-mode operation, optimization of performance and prediction code are adjusted with microcontroller unit (MCU). Monitoring mode is improved by x2.6 of figure-of-merits (FoM) that compared with previous resistive interface.clos

    A Low-Power Silicon-Photomultiplier Readout ASIC for the CALICE Analog Hadronic Calorimeter

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    The future e + e − collider experiments, such as the international linear collider, provide precise measurements of the heavy bosons and serve as excellent tests of the underlying fundamental physics. To reconstruct these bosons with an unprecedented resolution from their multi-jet final states, a detector system employing the particle flow approach has been proposed, requesting calorimeters with imaging capabilities. The analog hadron calorimeter based on the SiPM-on-tile technology is one of the highly granular candidates of the imaging calorimeters. To achieve the compactness, the silicon-photomultiplier (SiPM) readout electronics require a low-power monolithic solution. This thesis presents the design of such an application-specific integrated circuit (ASIC) for the charge and timing readout of the SiPMs. The ASIC provides precise charge measurement over a large dynamic range with auto-triggering and local zero-suppression functionalities. The charge and timing information are digitized using channel-wise analog-to-digital and time-to-digital converters, providing a fully integrated solution for the SiPM readout. Dedicated to the analog hadron calorimeter, the power-pulsing technique is applied to the full chip to meet the stringent power consumption requirement. This work also initializes the commissioning of the calorimeter layer with the use of the designed ASIC. An automatic calibration procedure has been developed to optimized the configuration settings for the chip. The new calorimeter base unit with the designed ASIC has been produced and its functionality has been tested

    A Low-Power, Reconfigurable, Pipelined ADC with Automatic Adaptation for Implantable Bioimpedance Applications

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    Biomedical monitoring systems that observe various physiological parameters or electrochemical reactions typically cannot expect signals with fixed amplitude or frequency as signal properties can vary greatly even among similar biosignals. Furthermore, advancements in biomedical research have resulted in more elaborate biosignal monitoring schemes which allow the continuous acquisition of important patient information. Conventional ADCs with a fixed resolution and sampling rate are not able to adapt to signals with a wide range of variation. As a result, reconfigurable analog-to-digital converters (ADC) have become increasingly more attractive for implantable biosensor systems. These converters are able to change their operable resolution, sampling rate, or both in order convert changing signals with increased power efficiency. Traditionally, biomedical sensing applications were limited to low frequencies. Therefore, much of the research on ADCs for biomedical applications focused on minimizing power consumption with smaller bias currents resulting in low sampling rates. However, recently bioimpedance monitoring has become more popular because of its healthcare possibilities. Bioimpedance monitoring involves injecting an AC current into a biosample and measuring the corresponding voltage drop. The frequency of the injected current greatly affects the amplitude and phase of the voltage drop as biological tissue is comprised of resistive and capacitive elements. For this reason, a full spectrum of measurements from 100 Hz to 10-100 MHz is required to gain a full understanding of the impedance. For this type of implantable biomedical application, the typical low power, low sampling rate analog-to-digital converter is insufficient. A different optimization of power and performance must be achieved. Since SAR ADC power consumption scales heavily with sampling rate, the converters that sample fast enough to be attractive for bioimpedance monitoring do not have a figure-of-merit that is comparable to the slower converters. Therefore, an auto-adapting, reconfigurable pipelined analog-to-digital converter is proposed. The converter can operate with either 8 or 10 bits of resolution and with a sampling rate of 0.1 or 20 MS/s. Additionally, the resolution and sampling rate are automatically determined by the converter itself based on the input signal. This way, power efficiency is increased for input signals of varying frequency and amplitude
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