Autocorrelation-based algorithm for single-frequency estimation

Authors:
Yang-Can Xiao;Ping Wei;Heng-Ming Tai
Affiliations:
School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 610054, China;School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 610054, China;Department of Electrical Engineering, University of Tulsa, Tulsa, OK 74104, USA
Venue:
Signal Processing
Year:
2007

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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.