  In this work, we propose a Fourier series-based approximation method using
ensemble Kalman filtering to estimate time-varying parameters in deterministic
dynamical systems. We demonstrate the capability of this approach in estimating
both sinusoidal and polynomial forcing parameters in a mass-spring system.
Results emphasize the importance of the choice of frequencies in the
approximation model terms on the corresponding time-varying parameter
estimates.
