Aiming at the full-wave Fourier and Kalman filter algorithms’ shortcomings of sensitive to frequency changes and poor ability of DC offset component reduction in the extraction of the fundamental component, a new fundamental component extraction algorithm is presented. First of all, this paper defines the DC offset component, fundamental angular frequency, fundamental component of the fault signal as state variables, and establishes the nonlinear state space model. Then, the Unscented Kalman Filter (UKF) is adopted to estimate the fundamental component based on the nonlinear model of signal. In addition, the filter algorithm is able to estimate the DC offset component and fundamental frequency in real-time. Several numerical simulations are carried out to testify the proposed algorithm and the results validate the algorithm''s feasibility and effectiveness. The simulation results show that the algorithm is adaptive to the sudden changes of frequency and DC offset component, and it can extract the fundamental component quickly and accurately.