Title
General method for sinusoidal frequencies estimation using ARMA algorithms with nonlinear prediction error transformation
Abstract
A new general approach to estimating the frequencies of sinusoidal signals corrupted by an additive nonGaussian noise is presented. The mixture of sinusoids and noise is modeled by an autoregressive moving average (ARMA) model with nonGaussian model noise. A class of ARMA recursive algorithms with nonlinear prediction error transformation is proposed for frequencies estimation. For a given probability density function of the model noise, known except for the scale parameter, the presented method enables the derivation of the algorithms ensuring the fastest convergence of the covariance error matrix to the asymptotic one. The robust version of the algorithms is also discussed. The performance of the ARMA nonlinear algorithms is illustrated by simulation results
Year
DOI
Venue
1992
10.1109/ICASSP.1992.226588
Acoustics, Speech, and Signal Processing, 1992. ICASSP-92., 1992 IEEE International Conference  
Keywords
DocType
Volume
filtering and prediction theory,parameter estimation,random noise,signal processing,spectral analysis,arma algorithms,additive nongaussian noise,autoregressive moving average,convergence,covariance error matrix,frequency estimation,nonlinear prediction error transformation,probability density function,recursive algorithms,sinusoidal signals,prediction algorithms,arma model,gaussian noise,moving average,prediction error,recursive algorithm
Conference
5
ISSN
Citations 
PageRank 
1520-6149
0
0.34
References 
Authors
5
3
Name
Order
Citations
PageRank
Platonov, A.A.100.34
Gajo, Z.K.200.34
Szabatin, J.300.34