Adaptive Blind Background Timing Mismatch Calibration for Sub-Nyquist Wideband Sampling

Sub-Nyquist sampling leverages the sparsity of wideband signals to sample below the Nyquist rate while preserving essential information. However, its performance is greatly affected by timing mismatches among sampling channels, especially in dynamic environments due to process, voltage, and temperature variations. Therefore, background calibration is desirable to rapidly track timing mismatches without interrupting normal sampling. However, traditional background calibration methods typically require a reference channel with a coprime sampling rate, which would introduce dynamic impedance interference and asynchronous sampling issues that lead to additional output spurs and higher power consumption. To address these issues, this letter proposes a data-driven blind background timing mismatch calibration approach that utilizes channel cross-correlation to adaptively estimate timing mismatches based on real-time measurements, and applies a Taylor series-based digital correction to compensate for mismatch signals. Numerical analyses show that the proposed calibration approach eliminates timing mismatch errors with faster convergence speed and higher accuracy.