A blind and adaptive method is proposed for time-interleaved analog-to-digital converter (TIADC) online mismatch correction. Firstly, a TIADC model is derived by transforming mismatches to FIR filters with different amplitudes and lags. Subsequently, residual error measure of corrected output for wide sense stationary input is built following cyclic autocorrelation function. Mismatches estimator could be obtained by minimizing the measure, in consequence, gain and timing mismatches correction could be achieved accurately via adjust parameterized filter adaptively. It is experimentally verified that the proposed method can enhance spurious-free dynamic range of TIADC output by 27~32dB. The proposed method can be used for online correction of gain and timing mismatch of TIADC with zero-mean wide stationary input.

A spectral parameterization method with discretization parameters will meet a tradeoff between the design accuracy and computational effort when designing a variable digital filter. Thus, a continuous spectral parameterization method is presented for obtaining the WLS optimal coefficients of variable fractional delay filters. Separated non-negative weighting function and some characters of matrix and matrix operations are applied to derive a closed-form solution, and Cholesky factorization is adopted to avoid the numerical problem of computing the inverses of a matrix. Its high accuracy and considerably reduced computational complexity of the proposed algorithm are experimentally verified. The given FIR filters can found their applications in high accuracy dynamic time compensation.