Square Root Unscented Digital Phased-locked Loop

Digital phase-locked loops (DPLLs) are widely used for synchronizing and estimating phase information. In DPLLs, the state estimator is a powerful method to estimate unknown phase information accurately. The Kalman filter (KF) is a well-known state estimator and has been employed to design DPLLs. However, the KF-based DPLL limited as it rsults in inaccurate modeling, including nonlinear effects (e.g., quantization error). The particle filter (PF) is a useful state estimator, but it incurs a large computation burden. In this paper, we propose a novel approach to design the square root unscented DPLL (SRUDPLL) in order to overcome the defects of the existing DPLLs. Through simulations, we demonstrate that the proposed method shows better performance than the existing approach in terms of nonlinear effects.

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