The IEEE Standard 1057 (IEEE-STD-1057) provides algorithms for fitting the
parameters of a sine wave to noisy discrete time observations. The fit is o
btained as an approximate minimizer of the sum of squared errors, i.e., the
difference between observations and model output. The contributions of thi
s paper include a comparison of the performance of the tour-parameter algor
ithm in the standard with the Cramer-Rao lower bound on accuracy, and with
the performance of a nonlinear least squares approach. It is shown that the
algorithm of IEEE-STD-1057 provides accurate estimates for Gaussian and qu
antization noise. In the Gaussian scenario it provides estimates with perfo
rmance close to the derived lower bound. In severe conditions with noisy da
ta covering only a fraction of a period, however, it is shown to have infer
ior performance compared with a one-dimensional (1-D) search of a concentra
ted cost function.