Accurate Frequency Estimator of Sinusoid Based on Interpolation of FFT and DTFT

An accurate frequency estimator of complex sinusoid in additive white noise is proposed. It is based on interpolation of Fast Fourier Transform (FFT) and Discrete-Time Fourier Transform (DTFT). Zero-padding is firstly performed before the FFT of the sinusoid sampled data, and the coarse estimate is...

Full description

Saved in:
Bibliographic Details
Published in:IEEE access 2020-01, Vol.8, p.1-1
Main Authors: Fan, Lei, Qi, Guoqing, Xing, Jun, Jin, Jiyu, Liu, Jinyu, Wang, Zhisen
Format: Article
Language:English
Subjects:
Additive white noise
Algorithms
Background noise
Correlation coefficient
Correlation coefficients
DTFT
Estimation
Fast Fourier transformations
FFT
Fourier transforms
Frequency estimation
Interpolation
Noise
Noise threshold
Signal to noise ratio
Sine waves
White noise
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:An accurate frequency estimator of complex sinusoid in additive white noise is proposed. It is based on interpolation of Fast Fourier Transform (FFT) and Discrete-Time Fourier Transform (DTFT). Zero-padding is firstly performed before the FFT of the sinusoid sampled data, and the coarse estimate is obtained by searching the discrete frequency index of the maximum FFT spectrum line. Then the fine estimate is obtained by employing the maximum FFT spectrum line and two DTFT sample values located on the left and right side of the maximum spectrum line. The correlation coefficients between the Fourier Transform of the noises on two arbitrarily spaced spectrum lines are derived, and the MSE calculation formula is derived in additive white noise background based on the correlation coefficients. Simulations results demonstrate that the proposed algorithm has lower MSE than the competing algorithms, and its signal-to-noise ratio (SNR) threshold is lower compared with Candan algorithm, AM algorithm and Djukanovic algorithms.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.2977978