Title
Autocorrelation-based algorithm for single-frequency estimation
Abstract
A novel iterative algorithm for estimating the frequency of a single complex sinusoid in the complex white Gaussian noise is proposed. Inspired by the works of Fitz, L&R, and the ILP approaches, the algorithm is based on the repeated use of an autocorrelation-based frequency estimator. This approach is different from the iterative linear prediction (ILP) algorithm, yet produces very comparable performance. Like the ILP algorithm, the proposed estimator has the reduced threshold, and its performance is close to that of the ML estimation and uniform across the frequency range of -@p to @p. In addition, the proposed estimator demonstrates an asymptotic error variance of 0.14dB above the CRB for N=1024 and 0.62dB for N=48, which is better than that of the ILP algorithm.
Year
DOI
Venue
2007
10.1016/j.sigpro.2006.10.012
Signal Processing
Keywords
DocType
Volume
complex white gaussian noise,ilp algorithm,single-frequency estimation,single complex sinusoid,novel iterative algorithm,proposed estimator,autocorrelation-based algorithm,iterative linear prediction,comparable performance,frequency range,autocorrelation-based frequency estimator,ilp approach,cramer rao bound,maximum likelihood,autocorrelation,white gaussian noise,iterative algorithm
Journal
87
Issue
ISSN
Citations 
6
Signal Processing
6
PageRank 
References 
Authors
0.59
9
3
Name
Order
Citations
PageRank
Yang-Can Xiao160.59
Ping Wei2253.81
Heng-Ming Tai323221.77