Computationally efficient parameter estimation for harmonic sinusoidal signals

A Markov-like weighted least squares (WLS) estimator is presented herein for harmonic sinusoidal parameter estimation. The estimator involves two distinct steps whereby it first obtains a set of initial parameter estimates that neglect the harmonic structure by some standard sinusoidal parameter estimation technique, and then the initial parameter estimates are refined via a WLS fit. Numerical results suggest that the proposed estimator achieves similar performance to the optimal nonlinear least-squares method for a moderate or large number of data samples and/or signal-to-noise ratio (SNR), but a significantly reduced computational complexity. Furthermore, the former is observed to have a lower threshold SNR than the latter.