Improvement of Extended Kalman Filter frequency tracker for nonstationary harmonic signals

Abstract

In this paper, we have considered a frequency tracking method based on Extended Kalman Filtering (EKF). The method uses a state space model to estimate and track the frequency of a harmonic signal embedded in broad-band noise. This signal is generally characterized by time-varying frequency and amplitude (nonstationary noisy harmonic signal). In this paper we have proposed a new state-space model for estimate and track the frequency of such nonstationary signals. The conventional EKF frequency trackers are typically characterized by a vector of three tuning parameters. With some assumptions and without any performance loss, we have proposed an EKF frequency tracker that only uses one tuning parameter. This simplification allows an easier and more transparent tuning of the EKF tracking behaviour.