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Investigation of the statistical method of time delay estimation based on conditional averaging of delayed signal

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper presents the results of the theoretical and practical analysis of selected features of the function of conditional average value of the absolute value of delayed signal (CAAV). The results obtained with the CAAV method have been compared with the results obtained by method of cross correlation (CCF), which is often used at the measurements of random signal time delay. The paper is divided into five sections. The first is devoted to a short introduction to the subject of the paper. The model of measured stochastic signals is described in Section 2. The fundamentals of time delay estimation using CCF and CAAV are presented in Section 3. The standard deviations of both functions in their extreme points are evaluated and compared. The results of experimental investigations are discussed in Section 4. Computer simulations were used to evaluate the performance of the CAAV and CCF methods. The signal and the noise were Gaussian random variables, produced by a pseudorandom noise generator. The experimental standard deviations of both functions for the chosen signal to noise ratio (SNR) were obtained and compared. All simulation results were averaged for 1000 independent runs. It should be noted that the experimental results were close to the theoretical values. The conclusions and final remarks were included in Section 5. The authors conclude that the CAAV method described in this paper has less standard deviation in the extreme point than CCF and can be applied to time delay measurement of random signals.
Rocznik
Strony
335--342
Opis fizyczny
Bibliogr. 19 poz., wykr., wzory
Twórcy
autor
autor
autor
  • Rzeszow University of Technology, Dept. of Metrology and Diagnostic Systems, W. Pola 2B, 35-959 Rzeszow, Poland, kowadam@prz.edu.pl
Bibliografia
  • [1] Bendat, J.S., Piersol, A.G. (2000). Random data - analysis and measurement procedures. John Wiley. New York.
  • [2] Bendat, J.S., Piersol, A.G. (1993). Engineering applications of correlation and spectral analysis. John Wiley. New York.
  • [3] Beck, M. S., Pląskowski, A. (1987). Cross-Correlation Flowmeters. Adam Hilger. Bristol.
  • [4] Blok, E. (2002). Classification and evaluation of discrete subsample time delay estimation algorithms. Proc. of 14th International Conference on Microwaves. Radar and Wireless Communications, 764-767.
  • [5] Carter, C.G. (1987). Coherence and time delay estimation. Proceedings of the IEEE, 75(2), 236-255.
  • [6] Jacovitti, G., Scarano, G (1993). Discrete time technique for time delay estimation. IEEE Transactions on Signal Processing, 41(2), 525-533.
  • [7] Lal-Jadziak, J. (2001). Accuracy in determination of correlation functions by digital methods. Metrology and Measurement Systems, 8(2), 153-164.
  • [8] Lal-Jadziak, J., Sienkowski, S. (2009). Variance of random signal mean square value digital estimator. Metrology and Measurement Systems, 16(2), 267-278.
  • [9] Piersol, A.G. (1981). Time delay estimation using phase data. IEEE Transactions on ASSP, 29(3), 471-477.
  • [10] Hanus, R. (2003). Statistical error analysis of time delay measurement by using phase of cross-spectral density function. Systems Analysis Modelling Simulation, 43(8), 993-998.
  • [11] Petryka, L., Hanus, R., Zych, M. (2008). Statistical signal analysis in the radioisotope two-phase flow measurements. PAK, 54(12), 866-868. (in Polish).
  • [12] Hanus, R. (2008). Statistical error comparison of time delay estimation using cross-correlation function and phase of cross-spectral density function. Electrical Review, 84(12), 301-303. (in Polish).
  • [13] Bendat, J.S. (1985). The Hilbert Transform and Applications to Correlation Measurements. Brüel&Kjær, BT0008-11. Naerum. Denmark.
  • [14] Cabot, R.C. (1981). A note on the application of the Hilbert transform to time delay estimation. IEEE Trans. Acoust. Speech. Signal Processing, 29, 607-609.
  • [15] Hanus, R. (2009). The application of the Hilbert transform to correlation measurements of time delay. Electrical Review, 85(7), 45-48. (in Polish).
  • [16] Kowalczyk, A. (1989). Regression method of velocity measurement. Educational and Scientific Equipment, 15(3-4), 34-36. (in Polish).
  • [17] Hanus, R. (2001). Accuracy comparison of some statistic methods of time delay measurements. Systems Analysis Modelling Simulation, 40(2), 239-244.
  • [18] Hanus, R., Kowalczyk, A. (2003). Estimators errors analysis of some statistical methods of time delay measurement. PAK, 49(7-8), 8-11. (in Polish).
  • [19] Kowalczyk, A., Szlachta, A. (2010). The application of conditional averaging of signals to obtain the transportation delay. Electrical Review, 86(1), 225-228. (in Polish).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BSW1-0079-0015
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