A novel frequency tracker for sinusoidal signal based on state dependent Riccati Equation filter

Abstract

This paper presents a new approach for frequency estimation and tracking based on State Dependent Riccati Equation Filter (SDREF). The SDREF is an alternative concept to the well-known Extended Kalman Filter (EKF) to design a robust nonlinear filter, with low computational costs and better performances. The aim is to estimate and track the time-varying fundamental frequency of harmonic sinusoidal signals in general and more particularly the fundamental electric frequency. Through this study, the performance of the proposed approach is compared to the widely adopted the EKF, taking into account several aspects both theoretically and real-life applications. It has been shown that the proposed estimator performs better than the usual EKF estimator in terms of noise robustness, estimation accuracy, and tracking ability both in numerical simulations and experimental study.