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Noniterative Frequency Estimator Based on Approximation of the WienerKhinchin Theorem
Cui YANG Lingjun LIU
Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Vol.E98A
No.4
pp.10211025 Publication Date: 2015/04/01
Online ISSN: 17451337
DOI: 10.1587/transfun.E98.A.1021
Type of Manuscript: LETTER Category: Digital Signal Processing Keyword: frequency estimation, autocorrelation lags, approximation of the WienerKhinchin theorem,
Full Text: PDF>>
Summary:
A closed form frequency estimator is derived for estimating the frequency of a complex exponential signal, embedded in white Gaussian noise. The new estimator consists of the fast Fourier transform (FFT) as the coarse estimation and the phase of autocorrelation lags as the finefrequency estimator. In the finefrequency estimation, autocorrelations are calculated from the powerspectral density of the signal, based on the WienerKhinchin theorem. For simplicity and suppressing the effect of noise, only the spectrum lines around the actual tone are used. Simulation results show that, the performance of the proposed estimator is approaching the CramerRao Bound (CRB), and has a lower SNR threshold compared with other existing estimators.

