Asymptotically minimum variance second-order estimation for complex circular processes

This paper addresses asymptotically minimum variance (AMV) of parameter estimators within the class of algorithms based on second-order statistics for estimating parameter of strict-sense stationary complex circular processes. As an application, the estimation of the frequencies of cisoids for mixed spectra time series containing a sum of cisoids and an MA process is considered.

[1]  Petre Stoica,et al.  Approximate maximum likelihood frequency estimation , 1994, Autom..

[2]  J. Magnus,et al.  Matrix Differential Calculus with Applications in Statistics and Econometrics , 1991 .

[3]  Ta-Hsin Li,et al.  Asymptotic normality of sample autocovariances with an application in frequency estimation , 1994 .

[4]  B. Friedlander,et al.  Asymptotic Accuracy of ARMA Parameter Estimation Methods based on Sample Covariances , 1985 .

[5]  P. J. Sherman,et al.  High resolution spectral estimation of sinusoids in colored noise using a modified Pisarenko decomposition , 1986, ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[6]  B. Friedlander,et al.  Performance analysis of parameter estimation algorithms based on high‐order moments , 1989 .

[7]  Jean Pierre Delmas Asymptotic normality of sample covariance matrix for mixed spectra time series: Application to sinusoidal frequencies estimation , 2001, IEEE Trans. Inf. Theory.

[8]  B. Friedlander,et al.  An approximate maximum likelihood approach to ARMA spectral estimation , 1985, 1985 24th IEEE Conference on Decision and Control.

[9]  P. Laguna,et al.  Signal Processing , 2002, Yearbook of Medical Informatics.

[10]  Björn E. Ottersten,et al.  Covariance Matching Estimation Techniques for Array Signal Processing Applications , 1998, Digit. Signal Process..

[11]  Benjamin Friedlander,et al.  Asymptotically optimal estimation of MA and ARMA parameters of non-Gaussian processes from high-order moments , 1990 .