On the application of cross correlation function to subsample discrete time delay estimation

2006 ◽  
Vol 16 (6) ◽  
pp. 682-694 ◽  
Author(s):  
Lei Zhang ◽  
Xiaolin Wu
Keyword(s):  
Correlation Function ◽  
Time Delay ◽  
Discrete Time ◽  
Cross Correlation ◽  
Time Delay Estimation ◽  
Cross Correlation Function ◽  
Delay Estimation ◽  
Discrete Time Delay

scholarly journals Time correlation techniques for subsample time delay estimation of complex signals based on polynomial interpolation.

2020 ◽  
Vol 2020 (12) ◽  
Author(s):  
O.A. Guschina ◽  
◽  
T.Ya. Shevgunov ◽  
Keyword(s):  
Correlation Function ◽  
Time Delay ◽  
Cross Correlation ◽  
Polynomial Interpolation ◽  
Time Correlation ◽  
Time Delay Estimation ◽  
Cross Correlation Function ◽  
Delay Estimation ◽  
Complex Signal ◽  
Complex Signals

This paper deals with the problem of subsample time delay estimation of complex signal based on polynomial interpolation. Time delay estimation is performed by cross-correlation time approach. Three polynomial interpolation techniques applied to the discrete complex cross-correlation function in the neighborhood of its maximum are proposed. These methods show high processing speed and allow obtaining accurate real-valued time delay estimation when digital complex signals are processed. The comparative analysis between these methods is performed. A rigorous analytical solution for the correction of time delay estimation for one of the proposed methods is obtained for the case of the third-order polynomial interpolation. This solution is applied for an equidistant grid of discrete cross-correlation function samples. One can improve the accuracy of time delay estimates by using aforementioned correction. A numerical simulation is performed to quantify the accuracy of the time delay estimates when using the proposed methods for the case where a stationary random process described by the first-order autoregressive mode is chosen as a model of original signal. The main results were presented and discussed at XIV All-Russian conference “Radar and telecommunication”.

Time Delay Estimation Based Discrete-Time Super-Twisting Current Control for a Six-Phase Induction Motor

2020 ◽  
Vol 35 (11) ◽  
pp. 12570-12580
Author(s):  
Yassine Kali ◽  
Magno Ayala ◽  
Jorge Rodas ◽  
Maarouf Saad ◽  
Jesus Doval-Gandoy ◽  
...  
Keyword(s):  
Time Delay ◽  
Induction Motor ◽  
Discrete Time ◽  
Time Delay Estimation ◽  
Current Control ◽  
Delay Estimation

scholarly journals Time Delay Estimation in Two-Phase Flow Investigation Using theγ-Ray Attenuation Technique

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Robert Hanus ◽  
Marcin Zych ◽  
Leszek Petryka ◽  
Dariusz Świsulski
Keyword(s):  
Time Delay ◽  
Cross Correlation ◽  
Two Phase Flow ◽  
Time Delay Estimation ◽  
Delay Estimation ◽  
Phase Flow ◽  
Two Phase ◽  
Stochastic Signals ◽  
Difference Function ◽  
Combined Methods

Time delay estimation is an important research question having many applications in a range of technologies. Measurement of a two-phase flow in a pipeline or an open channel using radioisotopes is an example of such application. For instance, the determination of velocity of dispersed phase in that case is based on estimation of the time delay between two stochastic signals provided by scintillation probes. The proper analysis of such signals, usually in presence of noise, requires the use of advanced statistical signal processing. In this paper, the simulation studies of time delay estimation were carried out with the use of the following differential methods: average magnitude difference function, and average square difference function and proposed combined methods comprising the above-mentioned differential and cross-correlation functions are presented. Attached simulations have been carried out for models of stochastic signals corresponding to the signals obtained in gamma-ray absorption measurements of gas-liquid flow in a horizontal pipeline. The standard uncertainties of time delay estimations have been determined for each of the methods. Improved metrological properties have been stated in the combined methods in comparison with the classical cross-correlation procedure.

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