Analysis and design of a wide dynamic range pulse-frequency modulation CMOS image sensor

Complementary Metal-Oxide Semiconductor (CMOS) image sensor is the dominant electronic imaging device in many application fields, including the mobile or portable devices, teleconference cameras, surveillance and medical imaging sensors. Wide dynamic range (WDR) imaging is of interest particular, demonstrating a large-contrast imaging range of the sensor. As of today, different approaches have been presented to provide solutions for this purpose, but there exists various trade-offs among these designs, which limit the number of applications. A pulse-frequency modulation (PFM) pixel offers the possibility to outperform existing designs in WDR imaging applications, however issues such as uniformity and cost have to be carefully handled to make it practical for different purposes. In addition, a complete evaluation of the sensor performance has to be executed prior to fabrication in silicon technology. A thorough investigation of WDR image sensor based on the PFM pixel is performed in this thesis. Starting with the analysis, modeling, and measurements of a PFM pixel, the details of every particular circuit operation are presented. The causes of dynamic range (DR) limitations and signal nonlinearity are identified, and noise measurement is also performed, to guide future design strategies. We present the design of an innovative double-delta compensating (DDC) technique which increases the sensor uniformity as well as DR. This technique achieves performance optimization of the PFM pixel with a minimal cost an improved linearity, and is carefully simulated to demonstrate its feasibility. A quad-sampling technique is also presented with the cooperation of pixel and column circuits to generate a WDR image sensor with a reduced cost for the pixel. This method, which is verified through the field-programmable gate array (FPGA) implementation, saves considerable area in the pixel and employs the maximal DR that a PFM pixel provides. A complete WDR image sensor structure is proposed to evaluate the performance and feasibility of fabrication in silicon technology. The plans of future work and possible improvements are also presented

A Low-Power Passive UHF Tag With High-Precision Temperature Sensor for Human Body Application

Radio frequency identification (RFID) tags are widely used in various electronic devices due to their low cost, simple structure, and convenient data reading. This topic aims to study the key technologies of ultra-high frequency (UHF) RFID tags and high-precision temperature sensors, and how to reduce the power consumption of the temperature sensor and the overall circuits while maintaining minimal loss of performance. Combined with the biomedicine, an innovative high-precision human UHF RFID chip for body temperature monitoring is designed. In this study, a ring oscillator whose output frequency is linearly related to temperature is designed and proposed as a temperature-sensing circuit by innovatively combining auxiliary calibration technology. Then, a binary counter is used to count the pulses, and the temperature is ultimately calculated. This topic designed a relaxation oscillator independent of voltage and current. The various types of resistors were used to offset the temperature deviation. A current mirror array calibration circuit is used to calibrate the process corner deviation of the clock circuit with a self-calibration algorithm. This study mainly contributes to reducing power consumption and improving accuracy. The total power consumption of the RF/analog front-end and temperature sensor is 7.65µW. The measurement error of the temperature sensor in the range of 0 to 60◦C is less than ±0.1%, and the accuracy of the output frequency of the clock circuit is ±2.5%

Low-Noise Energy-Efficient Sensor Interface Circuits

Today, the Internet of Things (IoT) refers to a concept of connecting any devices on network where environmental data around us is collected by sensors and shared across platforms. The IoT devices often have small form factors and limited battery capacity; they call for low-power, low-noise sensor interface circuits to achieve high resolution and long battery life. This dissertation focuses on CMOS sensor interface circuit techniques for a MEMS capacitive pressure sensor, thermopile array, and capacitive microphone. Ambient pressure is measured in the form of capacitance. This work propose two capacitance-to-digital converters (CDC): a dual-slope CDC employs an energy efficient charge subtraction and dual comparator scheme; an incremental zoom-in CDC largely reduces oversampling ratio by using 9b zoom-in SAR, significantly improving conversion energy. An infrared gesture recognition system-on-chip is then proposed. A hand emits infrared radiation, and it forms an image on a thermopile array. The signal is amplified by a low-noise instrumentation chopper amplifier, filtered by a low-power 30Hz LPF to remove out-band noise including the chopper frequency and its harmonics, and digitized by an ADC. Finally, a motion history image based DSP analyzes the waveform to detect specific hand gestures. Lastly, a microphone preamplifier represents one key challenge in enabling voice interfaces, which are expected to play a dominant role in future IoT devices. A newly proposed switched-bias preamplifier uses switched-MOSFET to reduce 1/f noise inherently.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/137061/1/chaseoh_1.pd

Electronics for Sensors

The aim of this Special Issue is to explore new advanced solutions in electronic systems and interfaces to be employed in sensors, describing best practices, implementations, and applications. The selected papers in particular concern photomultiplier tubes (PMTs) and silicon photomultipliers (SiPMs) interfaces and applications, techniques for monitoring radiation levels, electronics for biomedical applications, design and applications of time-to-digital converters, interfaces for image sensors, and general-purpose theory and topologies for electronic interfaces

The ATLAS TRT electronics

The ATLAS inner detector consists of three sub-systems: the pixel detector spanning the radius range 4cm-20cm, the semiconductor tracker at radii from 30 to 52 cm, and the transition radiation tracker (TRT), tracking from 56 to 107 cm. The TRT provides a combination of continuous tracking with many projective measurements based on individual drift tubes (or straws) and of electron identification based on transition radiation from fibres or foils interleaved between the straws themselves. This paper describes the on and off detector electronics for the TRT as well as the TRT portion of the data acquisition (DAQ) system

The ATLAS TRT electronics

Çetin, Serkant Ali (Dogus Author)The ATLAS inner detector consists of three sub-systems: the pixel detector spanning the radius range 4cm-20cm, the semiconductor tracker at radii from 30 to 52 cm, and the transition radiation tracker (TRT), tracking from 56 to 107 cm. The TRT provides a combination of continuous tracking with many projective measurements based on individual drift tubes (or straws) and of electron identification based on transition radiation from fibres or foils interleaved between the straws themselves. This paper describes the on and off detector electronics for the TRT as well as the TRT portion of the data acquisition (DAQ) system

New Architectures and Circuits for Pushing the Dynamic Range and Multiplexing Boundaries of CMOS-Integrated Sensors

Over the last decades, CMOS-integrated sensors have made impressive progress in performance, form-factor, and energy-efficiency for various applications such as imaging, physical/chemical sensing, bio/health monitoring. In the era of the artificial intelligence (AI) and the internet-of-things (IoT), such CMOS-integrated sensors are essential for massive and comprehensive data acquisition, where sensing range (or dynamic range), signal fidelity (or signal-to-noise ratio), and data throughput are key factors. Towards pushing the boundaries of such sensing capabilities, in this dissertation, novel sensing architectures are presented with energy/area-efficient circuit design techniques for multi-channel CMOS optical sensors and neural interfaces. The first topic is a fully-integrated, wide linear dynamic range optical sensor array combining linear and single-photon avalanche diode operation within each pixel. A pulse-counting readout scheme provides in-pixel digitization in an area-efficient manner for both operation modes, enabling fully parallel measurement across the array. The proposed dual-mode optical sensor array alternately requires high-voltage(10-20 V) and low-voltage supply (2-5 V) for reverse bias of the photodiodes, which is provided by a reconfigurable, closed-loop high-voltage charge pump in the same substrate. An 8 x 8 array architecture along with the dual-mode bias generator is fabricated in a general purpose 180 nm CMOS process and demonstrates 129 dB dynamic range while maintaining linear photoresponse operating with a dual-mode frame rate of 20 Hz. The second topic is a new approach for applying code-division multiplexing (CDM) to current-mode and voltage-mode sensor arrays with analog-domain orthogonal encoding directly in a shared, single analog-front-end circuit, which enables simultaneous readout for multiple sensors. The approach is applied to a 8 x 16 array of CMOS-integrated photodetectors and implemented in a general purpose 180 nm CMOS process, where the 16 channel CDM-based oversampling readout achieves an SNR improvement of more than 12 dB compared with time-division multiplexing at the same sampling rate. In addition, a CDM-based neural recording architecture is presented, which offers a significant tolerance to interference that can be injected through long cables

Southwest Research Institute assistance to NASA in biomedical areas of the technology utilization program

The activities are reported of the NASA Biomedical Applications Team at Southwest Research Institute between 25 August, 1972 and 15 November, 1973. The program background and methodology are discussed along with the technology applications, and biomedical community impacts