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Titolo:
COMPARISON OF THE PERFORMANCE OF 3 MAXIMUM DOPPLER FREQUENCY ESTIMATORS COUPLED WITH DIFFERENT SPECTRAL ESTIMATION METHODS
Autore:
MARASEK K; NOWICKI A;
Indirizzi:
POLISH ACAD SCI PL-00049 WARSAW POLAND
Titolo Testata:
Ultrasound in medicine & biology
fascicolo: 7, volume: 20, anno: 1994,
pagine: 629 - 638
SICI:
0301-5629(1994)20:7<629:COTPO3>2.0.ZU;2-9
Fonte:
ISI
Lingua:
ENG
Soggetto:
ULTRASOUND; BLOOD; SCATTERING; MODEL;
Keywords:
DOPPLER SPECTRUM; MAXIMUM FREQUENCY ESTIMATION; MEAN FREQUENCY ESTIMATION; SPECTRUM ANALYSIS; ARMA MODELING; AR MODELING;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Science Citation Index Expanded
Science Citation Index Expanded
Citazioni:
30
Recensione:
Indirizzi per estratti:
Citazione:
K. Marasek e A. Nowicki, "COMPARISON OF THE PERFORMANCE OF 3 MAXIMUM DOPPLER FREQUENCY ESTIMATORS COUPLED WITH DIFFERENT SPECTRAL ESTIMATION METHODS", Ultrasound in medicine & biology, 20(7), 1994, pp. 629-638

Abstract

The performance of three spectral techniques (FFT, AR Burg and ARMA) for maximum frequency estimation of the Doppler spectra is described. Different definitions of f(max) were used: frequency at which spectralpower decreases down to 0.1 of its maximum value, modified threshold crossing method (MTCM) and novel geometrical method. ''Goodness'' and efficiency of estimators were determined by calculating the bias and the standard deviation of the estimated maximum frequency of the simulated Doppler spectra with known statistics. The power of analysed signals was assumed to have the exponential distribution function. The SNR ratios were changed over the range from 0 to 20 dB. Different spectrumenvelopes were generated. A Gaussian envelope approximated narrow band spectral processes (P. W. Doppler) and rectangular spectra were usedto simulate a parabolic flow insonified with C. W. Doppler. The simulated signals were generated out of 3072-point records with sampling frequency of 20 kHz. The AR and ARMA models order selections were done independently according to Akaike Information Criterion (AIC) and Singular Value Decomposition (SVD). It was found that the ARMA model, computed according to SVD criterion, had the best overall performance and produced results with the smallest bias and standard deviation. In general AR(SVD) was better than AR(AIC). The geometrical method of f(max) estimation was found to be more accurate than other tested methods, especially for narrow band signals.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 27/09/20 alle ore 21:00:44