Asymptotically efficient estimation of spectral moments

This paper studies parametric estimation of spectral moments of a zero-mean complex Gaussian stationary process immersed in independent Gaussian noise. With the merit of the maximum-likelihood (ML) approach as motivation, this work exploits a Whittle’s type objective function able to capture the relevant features of the log-likelihood function, while being much more manageable. The resulting estimates are strongly consistent and asymptotically efficient. As an example, application to Doppler weather radar data is considered. EDICS category: 3.6.1 Parameter Estimation: Single-Channel Time Series.