Least square and Kalman based methods for dynamic phasor estimation: a review

摘要

The characterization of sinusoidal signals with time varying amplitude and phase is useful and applicable for many fields. Therefore several algorithms have been suggested to estimate main aspects of these signals. Within no standard approach to test the properties of these algorithms, it seems to be helpful to discuss a large class of algorithms according to their properties. In this paper, six methods of estimating dynamic phasor have been reviewed and discussed which three of them are based on least square and others are based on Kalman filter. Taylor expansion is used as a first step and continued with least square or Kalman filter in accordance with the proposal observer of each method. The theoretical processes of these methods are briefly clarified. The characterizations have been made by some tests in time and frequency domains. The tests include amplitude step, phase step, frequency step, frequency response, total vector error, transient monitor, noise, sample number, computation time, harmonic and DC offset which build a framework to compare the different methods.