Nonlinear filtering methods for harmonic retrieval

The authors address the problem of high-resolution parameter estimation of superimposed sinusoids using nonlinear filtering techniques. Six separate nonlinear filters are evaluated for the estimation of the parameters of sinusoids in white and colored Gaussian noise. Experimental evaluation demonstrates that the nonlinear filters perform very satisfactorily (close to the Cramer-Rao bound) for reasonable values of the initial estimation error. A major advantage of using nonlinear filtering methods for harmonic retrieval is that the filters can be applied to time-varying process models as well.<>