On signal-to-noise ratio estimation

A new simple algorithm for estimating signal-to-noise ratio (SNR) for a signal consisting of one sinusoid in white Gaussian noise is proposed in this paper. Algorithm is based on autocorrelation and modified covariance methods for AR (Autoregressive) spectral estimation. The validity of the algorith...

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Bibliographic Details
Main Authors: Papic, Veljko, Djurovic, Zeljko, Kvascev, Goran, Tadic, Predrag
Format: Conference Proceeding
Language:English
Subjects:
Amplitude estimation
Autocorrelation
Communication industry
Frequency estimation
Gaussian noise
Phase noise
Power system harmonics
Power system simulation
Signal processing algorithms
Signal to noise ratio
Online Access:Request full text
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Summary:A new simple algorithm for estimating signal-to-noise ratio (SNR) for a signal consisting of one sinusoid in white Gaussian noise is proposed in this paper. Algorithm is based on autocorrelation and modified covariance methods for AR (Autoregressive) spectral estimation. The validity of the algorithm is examined by comparing its SNR estimate with SNR estimate obtained by sinusoid magnitude estimation using Pisarenko harmonic decomposition method and noise variance estimation using modified covariance method. By a large number of simulations this algorithm has proven itself as a comparably precise even in case of significantly noise-contaminated sinusoidal signal.
ISSN:2158-8473
2158-8481
DOI:10.1109/MELCON.2010.5476314