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 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.