A Fast Mismatch Calibration Method Based on Frequency Domain Orthogonal Decomposition for Time-Interleaved Analog-to-Digital Converters

Abstract

This paper proposes a fully digital background calibration method for time-interleaved analog-to-digital converter (TIADC) mismatches. The method analyzes the frequency and phase of spurious signals caused by three types of mismatches in TIADCs in the frequency domain. By utilizing the Hilbert transform and frequency shifting, orthogonal basis signals located at the mismatch frequencies can be constructed. The calibration of mismatches is achieved by linearly combining the orthogonal basis signals with the estimated coefficients and subtracting them from the original signal. The estimation of coefficients is determined by evaluating the correlation between the linear combination of orthogonal basis signals and the calibrated signal. Furthermore, an exponential moving average (EMA) and least mean square (LMS) algorithm are introduced to expedite the coefficient estimation process. The entire calibration process converges in merely 600 samples, significantly improving the convergence speed. By monitoring the amplitude of the input signal and adjusting the LMS step, the algorithm is functional under different amplitude signals, enhancing the robustness. An off-chip calibration is conducted based on a commercial 14-bit, 8-channel, 2.4GSPS TIADC. Results indicate that all spurious signals are suppressed below 80 dB, and the convergence rate is consistent with the simulation.