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Adaptive Filtering of Non Stationary Signals for Frequency Estimation Using hybrid KDE


B. N. Biswal, S. C. Satapathy, P .K. Patra, G.Panda


Vol. 11  No. 6  pp. 288-294


The paper highlights a novel hybrid EKF (Extended Kalman Filter) and Differential evolution (DE) called KDE (Kalman differential evolution) approach for tracking Parameters of a signal corrupted with noise and harmonics. The modeling and measurement of error covariance matrices Q and R are optimized using differential evolution. A new adaptive filtering technique is employed for self adaption of mutation scale factor in DE. To improve the convergence speed of optimization process K-DE, a variant of standard DE is considered for the optimization of Q and R matrices. Simulation results for time varying frequency of the power signal reveal significant improvement in noise rejection and accuracy in obtaining the frequency of the signal.


Differential evolution, Extended Kalman filters, covariance, Kalman Differential Evolution