• JSTS:Journal of Semiconductor Technology and Science
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• v.17 no.1
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• pp.110-119
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• 2017

This paper describes a CMOS image sensor (CIS) with dual correlated double sampling (CDS) and column-parallel analog-to-digital converter (ADC) and its measurement method using a field-programmable gate array (FPGA) integrated module. The CIS is composed of a $320{\times}240$ pixel array with $3.2{\mu}m{\times}3.2{\mu}m$ pixels and column-parallel 10-bit single-slope ADCs. It is fabricated in a $0.11-{\mu}m$ CIS process, and consumes 49.2 mW from 1.5 V and 3.3 V power supplies while operating at 6.25 MHz. The measured dynamic range is 53.72 dB, and the total and column fixed pattern noise in a dark condition are 0.10% and 0.029%. The maximum integral nonlinearity and the differential nonlinearity of the ADC are +1.15 / -1.74 LSB and +0.63 / -0.56 LSB, respectively.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.8
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• pp.1255-1259
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• 1990

A new ripple analog-to-digital converter (ADC) has been developed. It consists of two parallel ADCs and a switching network. The circuit operates on the analog input signal in two serial steps. First, a coarse conversion is made to determine the most significant bits by the first parallel ADC. The resultant bits control the switching network to connect a series resistor segment, within which the analog signal is contained, to the second parallel ADC. At second step, a fine conversion is made to determine the least significant bits by the second parallel ADC. The circuit requires 2(2\ulcorner\ulcorner1) comparators, 2(2\ulcorner\ulcorner resistors, and 2(2\ulcorner\ulcorner swithches for N-bit resolution.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.571-573
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• 1988

A new ripple analog-to-digital converter(ADC) has been developed. It consists of two parallel ADCs and a switching network. The circuit operates on the input signal in two serial steps. First a coarse conversion is made to determine the most significant bits by the first parallel ADC. The results control a switching network to connect the series resistor segment, the analog signal is contained within, to the second parallel ADC. At second step, a fine conversion is made to determine the least signification bits by the second parallel ADC. The circuit requires 2(2$\frac{N}{2}$) comparators, 2(2$\frac{N}{2}$) resistors, and 2(2$\frac{N}{2}$) switches for N-bit resolution.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.538-540
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• 2004

Electrical currents generated by human heart activities create magnetic fields represented by MCG(MagnetoCardioGram). Since an MCG signal acquisition system requires precise and stable operation, the system adopts hundreds of SQUID(Superconducting QUantum Interface Device) sensors for signal acquisition. Such a system requires fast real-time data acquisition in a required sampling interval, i.e., 1 mili-second for each sensor. This paper presents designed hardware to acquire data from 256-channel analog signal with 1 ksamples/sec speed, using 12-bit 8-channel ADC devices, SPI interfaces, parallel interfaces, 8-bit microprocessors, and a DSP processor. We implemented SPI interface between ADCs and a microprocessor, parallel interfaces between microprocessors. Our result concludes that the data collection can be done in $168{\mu}sec$ time-interval for 256 SQUID sensors, which can be interpreted to 6 ksamples/sec speed.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.07b
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• pp.902-905
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• 2004

A heart diagnosis system adopts Superconducting Quantum Interface Device(SQUID) sensors for precision MCG signal acquisitions. Such system is composed of hundreds of sensors, requiring fast signal sampling and precise analog-digital conversions(ADC). Our development of hardware board, processing 64-channel 12-bit 1ks/s, is built by using 8-channel ADC chips, 8-bit microprocessors, SPI interfaces, and parallel data transfers between microprocessors to meet the 1ks/s, i.e. 1 ms speed. The test result shows that the signal acquisition is done in 168 usuc which is much shorter than the required 1 ms period. This hardware will be extended to 256 channel data acquisition to be used for the diagnosis system.

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.1
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• pp.22-28
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• 2015

This paper proposes column-parallel three step Single Slope Analog-to-Digital Converter (SS-ADC) for high frame rate VGA CMOS Image Sensors (CISs). The proposed three step SS-ADC improves the sampling rate while maintaining the architecture of the conventional SS-ADC for high frame rate CIS. The sampling rate of the three-step ADC is increased by a factor of 39 compared with the conventional SS-ADC. The proposed three-step SS-ADC has a 12-bit resolution and 200 kS/s at 25 MHz clock frequency. The VGA CIS using three step SS-ADC has the maximum frame rate of 200 frames/s. The total power consumption is 76 mW with 3.3 V supply voltage without ramp generator buffer. A prototype chip was fabricated in a $0.13{\mu}m$ CMOS process.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.385-390
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• 2006

This paper examines the sampling and jitter specifications and considerations for Global Navigation Satellite Systems (GNSS) software receivers. Software radio (SWR) technologies are being used in the implementation of communication receivers in general and GNSS receivers in particular. With the advent of new GPS signals, and a range of new Galileo and GLONASS signals soon becoming available, GNSS is an application where SWR and software-defined radio (SDR) are likely to have an impact. The sampling process is critical for SWR receivers, where it occurs as close to the antenna as possible. One way to achieve this is by BandPass Sampling (BPS), which is an undersampling technique that exploits aliasing to perform downconversion. BPS enables removal of the IF stage in the radio receiver. The sampling frequency is a very important factor since it influences both receiver performance and implementation efficiency. However, the design of BPS can result in degradation of Signal-to-Noise Ratio (SNR) due to the out-of-band noise being aliased. Important to the specification of both the ADC and its clocking Phase- Locked Loop (PLL) is jitter. Contributing to the system jitter are the aperture jitter of the sample-and-hold switch at the input of ADC and the sampling-clock jitter. Aperture jitter effects have usually been modeled as additive noise, based on a sinusoidal input signal, and limits the achievable Signal-to-Noise Ratio (SNR). Jitter in the sampled signal has several sources: phase noise in the Voltage-Controlled Oscillator (VCO) within the sampling PLL, jitter introduced by variations in the period of the frequency divider used in the sampling PLL and cross-talk from the lock line running parallel to signal lines. Jitter in the sampling process directly acts to degrade the noise floor and selectivity of receiver. Choosing an appropriate VCO for a SWR system is not as simple as finding one with right oscillator frequency. Similarly, it is important to specify the right jitter performance for the ADC. In this paper, the allowable sampling frequencies are calculated and analyzed for the multiple frequency BPS software radio GNSS receivers. The SNR degradation due to jitter in a BPSK system is calculated and required jitter standard deviation allowable for each GNSS band of interest is evaluated. Furthermore, in this paper we have investigated the sources of jitter and a basic jitter budget is calculated that could assist in the design of multiple frequency SWR GNSS receivers. We examine different ADCs and PLLs available in the market and compare known performance with the calculated budget. The results obtained are therefore directly applicable to SWR GNSS receiver design.