A Novel Particle Filter-based Digital Phase-locked Loop Robust Against Quantization Error

Abstract

Using digital phase-locked loops (DPLL) is an efficient way of estimating phase information. To obtain accurate phase information, the Kalman filter (KF) has become a powerful tool in many applications. In digital systems, the DPLL measurement is transformed into a quantized measurement. During this process, missing measurement information, known as quantization errors, certainly occurs. However, quantization errors are an inevitable problem in digital system implementation, where the KF-based DPLL (KFDPLL) may show poor estimation performance. In order to estimate accurate phase information in the presence of quantization errors, we propose a particle filter-based DPLL (PFDPLL) to overcome the poor performance of the KFDPLL. Through numerical examples, we show that the PFDPLL is more robust against quantization errors than the KFDPLL.