"Applying the ""Split-ADC"" Architecture to a 16 bit, 1 MS/s differential Successive Approximation Analog-to-Digital Converter"

Chan, Ka Yan

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"Applying the ""Split-ADC"" Architecture to a 16 bit, 1 MS/s differential Successive Approximation Analog-to-Digital Converter"

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Successive Approximation (SAR) analog-to-digital converters are used extensively in biomedical applications such as CAT scan due to the high resolution they offer. Capacitor mismatch in the SAR converter is a limiting factor for its accuracy and resolution. Without some form of calibration, a SAR converter can only achieve 10 bit accuracy. In industry, the CAL-DAC approach is a popular approach for calibrating the SAR ADC, but this approach requires significant test time. This thesis applies the ""Split-ADC"" architecture with a deterministic, digital, and background self-calibration algorithm to the SAR converter to minimize test time. In this approach, a single ADC is split into two independent halves. The two split ADCs convert the same input sample and produce two output codes. The ADC output is the average of these two output codes. The difference between these two codes is used as a calibration signal to estimate the errors of the calibration parameters in a modified Jacobi method. The estimates are used to update calibration parameters are updated in a negative feedback LMS procedure. The ADC is fully calibrated when the difference signal goes to zero on average. This thesis focuses on the specific implementation of the ""Split-ADC"" self-calibrating algorithm on a 16 bit, 1 MS/s differential SAR ADC. The ADC can be calibrated with 105 conversions. This represents an improvement of 3 orders of magnitude over existing statistically-based calibration algorithms. Simulation results show that the linearity of the calibrated ADC improves to within Â±1 LSB.

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