Approximate Maximum-Likelihood Algorithms for Two-Dimensional Frequency Estimation of a Complex Sinusoid

Author

So, Hing Cheung ; Chan, Frankie Kit Wing

Author_Institution

Dept. of Electron. Eng., City Univ. of Hong Kong

Volume

54

Issue

8

fYear

2006

Firstpage

3231

Lastpage

3237

Abstract

Starting with the maximum-likelihood (ML) formulation, three iterative algorithms for approximate ML frequency estimation of a two-dimensional (2-D) complex sinusoid in white Gaussian noise are developed. Mean and variance analyses of the proposed methods are provided, which show that they are approximately unbiased and their performance achieves Cramer-Rao lower bound (CRLB) at sufficiently high signal-to-noise ratio (SNR) conditions. Computer simulation results are included to corroborate the theoretical development as well as to contrast the performance of the proposed algorithms with Kay´s estimators and the CRLB

Keywords

Gaussian noise; frequency estimation; iterative methods; maximum likelihood estimation; white noise; Cramer-Rao lower bound; SNR; approximate maximum-likelihood frequency estimation; iterative algorithms; mean analysis; signal-to-noise ratio; two-dimensional complex sinusoid; two-dimensional frequency estimation; variance analysis; white Gaussian noise; Analysis of variance; Computer simulation; Frequency estimation; Gaussian noise; Iterative algorithms; Maximum likelihood estimation; Performance analysis; Signal analysis; Signal to noise ratio; Two dimensional displays; Frequency estimation; iterative algorithm; linear prediction; maximum-likelihood estimation;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/TSP.2006.877654

Filename

1658274