Title :
On SNR estimation using IEEE-STD-1057 three-parameter sine wave fit
Author :
Negusse, Senay ; Handel, Peter ; Zetterberg, Per
Author_Institution :
Signal Process. Lab., ACCESS Linnaeus Center, Stockholm, Sweden
Abstract :
In this paper, theoretical properties of a maximum-likelihood (ML) estimator of signal-to-noise ratio (SNR) is discussed. The three-parameter sine fit algorithm is employed on a finite and coherently sampled measurement set corrupted by additive white Gaussian noise. Under the Gaussian noise model, the least squares solution provided by the three-parameter sine fit is also ML estimator. Exact distribution and finite sample properties of the SNR estimate are derived. Moreover, an explicit expression for the mean squared error (MSE) of the estimator is given. Simulation results are shown to verify the underlying theoretical results.
Keywords :
AWGN; IEEE standards; least mean squares methods; maximum likelihood estimation; measurement standards; signal sampling; waveform generators; IEEE-STD-1057; ML estimator; SNR estimation; additive white Gaussian noise; coherently sampled measurement set; finite sampled measurement; least mean squared error method; maximum likelihood estimation; parameter sine fit algorithm; signal-to-noise ratio; Histograms; Maximum likelihood estimation; Signal processing algorithms; Signal to noise ratio; Vectors; Signal-to-Noise Ratio; Sine-fit algorithm; coherent sampling; maximum-likelihood;
Conference_Titel :
Instrumentation and Measurement Technology Conference (I2MTC), 2013 IEEE International
Conference_Location :
Minneapolis, MN
Print_ISBN :
978-1-4673-4621-4
DOI :
10.1109/I2MTC.2013.6555497
