Abstract
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.
Original language | English |
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Pages (from-to) | 1937-1944 |
Number of pages | 8 |
Journal | Signal Processing |
Volume | 80 |
Issue number | 9 |
DOIs | |
State | Published - Sep 2000 |