Calibration of static nonlinearity mismatch errors in TIADC based on periodic time-varying adaptive method

Abstract

The nonlinear behaviors of time-interleaved analog-to-digital converter (TIADC) caused by non-ideal circuit implementations degrade performance of TIADC significantly. This paper proposes a calibration method based on model inversion strategy to compensate for static nonlinearities in TIADC, since static nonlinearities are the major compositions of the nonlinear behaviors in most situations. The proposed periodic time-varying adaptive calibration method can estimate coefficients of inverse polynomial model directly and capture variations of the nonlinear parameters when environment changes. The method proposed in this paper is also applicable to dynamic nonlinearities by changing polynomial with Volterra series. Simulation results show the effectiveness and robustness of the proposed method.