ADC Characterization

This work is aimed to characterize and develop a calibration methodology to compensate pipeline analog-digital converters (ADC)s. In this work the integral nonlinearity (INL) is characterized, modeled and used to develop one new method in order to obtain a calibration sequence. One of the most important ADC characteristics is the INL. The INL describes the deviation between the ideal output of an ADC and the current output level. The INL has a dynamic behavior since it depends on input signal characteristics. The INL model can be subdivided into two components: the low code frequency (LCF) and the high code frequency (HCF). The HCF is a static term that depends only on the output code k and is related to the ADC circuitry imperfections. We will not model the HCF in the work. The dynamic part is the LCF and depends on the input signal characteristics. The LCF is modeled by a polynomial of order L depending on frequency m and the output code k.  The harmonics of the ADC digital output are related to the LCF part of the INL. In this work, we will optimize the LCF and use it to calibrate the first and higher Nyquist bands of a pipeline ADC. The basic idea of this model is to obtain an error sequence by an optimization process done in the frequency domain. The optimal LCF frequency-dependent coefficients are computed in an iterative process until the harmonics of the output spectrum are minimized. In the calibration process, the HCF part is used as a static look-up-table (LUT) and the dynamic part is performed using a frequency-dependent LCF polynomial coefficients. This optimization model gives notably better results than the INL model. The harmonics in the three first Nyquist bands are attenuated using the model explained in this work.