Adaptive Background Estimation for Static Nonlinearity Mismatches in Two-Channel TIADCs

Abstract

Due to channel mismatches in time-interleaved analog-to-digital converters (TIADCs), estimation and compensation methods are required to restore the resolution of the individual converters. Whereas several methods exist for linear mismatches, nonlinearity mismatches have not been widely investigated. This brief presents an adaptive background estimation method for nonlinearity mismatches in two-channel TIADCs. It utilizes a normalized least-mean-square algorithm and assumes slight oversampling as well as a polynomial nonlinearity model that is appropriate when smooth errors dominate. Furthermore, two implementation strategies are proposed to enhance its ability for different applications. The estimation performance of the proposed method is evaluated through behavioral-level simulations.