Before revision:  We present an approach to estimate periodic, time-varying parameters using nonlinear Bayesian filtering. Most parameter estimation methodology in the literature is aimed at estimating constant parameters or parameters whose values drift over time with no imposed structure. The proposed technique imposes periodic structure by treating the time-varying parameter as a piecewise function with unknown coefficients , estimated using the ensemble Kalman filter (EnKF) .
After revision:  We present an approach to estimate periodic, time-varying parameters that imposes periodic structure by treating the time-varying parameter as a piecewise function with unknown coefficients , estimated using the ensemble Kalman filter (EnKF) .