Accuracy analysis of the normalized frequency estimation of a discrete-time sine-wave by the average-based interpolated DFT method

Abstract The normalized frequency of a sine-wave can be estimated by the average of the two estimates achieved using the Interpolated Discrete Fourier Transform (IpDFT) method. This approach is called average-based IpDFT method. The paper investigates the effect of the spectral interference from the image component and additive wideband noise on the accuracy of the normalized frequency estimator provided by the average-based IpDFT method with maximum sidelobe decay windows in the case of a discrete-time sine-wave. The expressions of the maximum of the normalized frequency estimator error due to the spectral interference and variance of the normalized frequency estimator due to the wideband noise are derived. Also, the expression of the combined standard uncertainty of the normalized frequency estimator is derived. The accuracies of all derived expressions are confirmed by means of computer simulations. Moreover, the performance of the average-based IpDFT method is compared with those of a state-of-the-art three-point IpDFT method and IpDFT method through both computer simulations and experimental results.

[1]  Jozef Borkowski,et al.  LIDFT method with classic data windows and zero padding in multifrequency signal analysis , 2010 .

[2]  D. Petri,et al.  The influence of windowing on the accuracy of multifrequency signal parameter estimation , 1992 .

[3]  Martin Novotný,et al.  Uncertainty Analysis of the RMS Value and Phase in the Frequency Domain by Noncoherent Sampling , 2007, IEEE Transactions on Instrumentation and Measurement.

[4]  Daniel Belega,et al.  Statistical description of the sine-wave frequency estimator provided by the interpolated DFT method , 2012 .

[5]  A. Nuttall Some windows with very good sidelobe behavior , 1981 .

[6]  J. Borkowski,et al.  LIDFT-the DFT linear interpolation method , 2000, IEEE Trans. Instrum. Meas..

[7]  Daniel Belega,et al.  Frequency estimation via weighted multipoint interpolated DFT , 2008 .

[8]  D. C. Rife,et al.  Use of the discrete fourier transform in the measurement of frequencies and levels of tones , 1970, Bell Syst. Tech. J..

[9]  G. Andria,et al.  Windows and interpolation algorithms to improve electrical measurement accuracy , 1989 .

[10]  D. Belega,et al.  Multifrequency signal analysis by Interpolated DFT method with maximum sidelobe decay windows , 2009 .

[11]  Daniel Belega,et al.  Accuracy of Sine Wave Frequency Estimation by Multipoint Interpolated DFT Approach , 2010, IEEE Transactions on Instrumentation and Measurement.

[12]  D. Dallet,et al.  Uncertainty analysis of the normalized frequency estimation of a sine wave by three-point Interpolated DFT method , 2008, 2008 IEEE International Workshop on Advanced Methods for Uncertainty Estimation in Measurement.

[13]  Dario Petri,et al.  Interpolation techniques for real-time multifrequency waveform analysis , 1989 .

[14]  Dusan Agrez,et al.  Weighted multipoint interpolated DFT to improve amplitude estimation of multifrequency signal , 2002, IEEE Trans. Instrum. Meas..

[15]  Kui Fu Chen,et al.  Against the long-range spectral leakage of the cosine window family , 2009, Comput. Phys. Commun..

[16]  Kui Fu Chen,et al.  Composite Interpolated Fast Fourier Transform With the Hanning Window , 2010, IEEE Transactions on Instrumentation and Measurement.

[17]  Yan Feng Li,et al.  Combining the Hanning windowed interpolated FFT in both directions , 2008, Comput. Phys. Commun..