The Causes of Leakage Deviations from Sinc Function in DFT and Ways to Minimize Them

Authors

  • Karel Hájek Department of Electrical Engineering, University of Defence in Brno, Czech Republic

DOI:

https://doi.org/10.3849/aimt.01375

Keywords:

aliasing, DFT, frequency estimation, leakage

Abstract

The article describes new model for a solution to the instability problem of DFT spectra leakage for the incoherent real sinusoidal signal, which is a fundamental problem, for example when solving the most accurate estimation of its frequency in various types of measurement practical tasks. It shows that the main cause of leakage deviations from the sync function is aliasing, which, together with an undefined value of the input signal phase, causes a seemingly random deviation of leakage. This paper shows it by a new form of DFT spectrum expression. It consists mainly of the spectrum of the rectangular signal in the form of the function sinc, modulated to the frequency of the tested signal in baseband. To do this, analogous spectra from other neighbouring bands formed by the sampling effect are added as aliasing. In doing so, the effect of adding or subtracting the phase of the test signal is reflected, depending on the signal parameters. Based on the analysis of these effects, some ways to minimize or correct them are shown. On the other hand, the paper shows a simpler and substantially lesser effect of aliasing in the DFT spectrum for a complex sinusoidal signal.

Author Biography

  • Karel Hájek, Department of Electrical Engineering, University of Defence in Brno, Czech Republic

    Electrical Engineering

References

OPPENHEIM, A.V. and SCHAFER, R.V. Discrete-Time Signal Processing. 3rd ed. London: Pearson, 2009. 1144 p. ISBN 978-0-13-198842-2.

LYONS, R.G. Understanding Digital Signal Processing. 2nd ed. New Jersey: Prentice Hall, 2004. 688 p. ISBN 978-0-13-108989-1.

SMITH, S.W. The Scientist and Engineer’s Guide to Digital Signal Processing. 2nd ed. San Diego: California Technical Publishing, 1999. 664 p. ISBN 978-0-96-601767-0.

ROBERTS, M.J. Signals and Systems: Analysis Using Transform Methods and MATLAB®. New York: McGraw Hill, 2003. 1072 p. ISBN 978-0-07-249942-1.

ZIELIŃSKI, T.P. and DUDA, K. Frequency and Damping Estimation Methods – an Overview. Metrology and Measurement Systems, 2011, vol. 18, no. 4, p. 505-528. https://doi.org/10.2478/v10178-011-005-y.

DJUKANOVIĆ, S. An Accurate Method for Frequency Estimation of a Real Sinusoid. IEEE Signal Processing Letters, 2016, vol. 23, no. 7, p. 915-918. https://doi.org/10.1109/LSP.2016.2564102.

LUO, J., HOU, S., LI, X., OUYANG, Q. and ZHANG, Y. Generalization of Interpolation DFT Algorithms and Frequency Estimators with high Image Component Interference Rejection. EURASIP Journal on Advances in Signal Processing, 2016, Article number 30. https://doi.org/10.1186/s13634-016-0330-6.

BELEGA, D., PETRI, D. and DALLET, D. Frequency Estimation of a Sinusoidal Signal via a Three-Point Interpolated DFT Method with High Image Component Interference Rejection Capability. Digital Signal Processing, 2014, vol. 24, p. 162-169. https://doi.org/10.1016/j.dsp.2013.09.014.

RADIL, T., RAMOS, P.M. and SERRA, A.C. New Spectrum Leakage Correction Algorithm for Frequency Estimation of Power System Signals. IEEE Transactions on Instrumentation and Measurement, 2009, vol. 58, no. 5, p. 1670-1679. https://doi.org/10.1109/TIM.2009.2014506.

CANDAN, C. A Method for Fine Resolution Frequency Estimation from Three DFT Samples. IEEE Signal Processing Letters, 2011, vol. 18, no. 6, p. 351-354. https://doi.org/10.1109/LSP.2011.2136378

CANDAN, C. Analysis and Further Improvement of Fine Resolution Frequency Estimation Method from Three DFT Samples. IEEE Signal Processing Letters, 2013, vol. 20, no. 9, p. 913-916. https://doi.org/10.1109/LSP.2013.2273616.

CANDAN, C. Fine Resolution Frequency Estimation from Three DFT Samples: Case of Windowed Data. Signal Processing, 2015, vol. 114, p. 245-250. https://doi.org/10.1016/j.sigpro.2015.03.009.

LIAO, J.-R. and LO, S. Analytical Solutions for Frequency Estimators by Interpolation of DFT Coefficients. Signal Processing, 2014, vol. 100, p. 93-100. https://doi.org/10.1016/j.sigpro.2014.01.012.

LIAO, J.-R. and CHEN, C.-M. Phase Correction of Discrete Fourier Transform Coefficients to Reduce Frequency Estimation Bias of Single Tone Complex Sinusoid. Signal Processing, 2014, vol. 94, p. 108-117. https://doi.org/10.1016/j.sigpro.2013.05.021.

XIANG, J., CUI, W. and SHEN, Q. Flexible and Accurate Frequency Estimation for Complex Sinusoid Signal by Interpolation Using DFT Samples. Chinese Journal of Electronics, 2018, vol. 27, no. 1, p. 109-114. https://doi.org/10.1049/cje.2017.09.019.

DUDA, K. and BARCZENTEWICZ, S. Interpolated DFT for sinα(x) Windows. IEEE Transactions on Instrumentation and Measurement, 2014, vol. 63, no. 4, p. 754-760. https://doi.org/10.1109/TIM.2013.2285795.

DUDA, K. DFT Interpolation Algorithm for Kaiser–Bessel and Dolph-Chebyshev Windows. IEEE Transactions on Instrumentation and Measurement, 2011, vol. 60, no. 3, p. 784-790. https://doi.org/10.1109/TIM.2010.2046594.

WERNER, K.J. and GERMAIN, F.G. Sinusoidal Parameter Estimation Using Quadratic Interpolation around Power-Scaled Magnitude Spectrum Peaks. Applied Sciences, 2016, vol. 6, no. 10, p. 1-22. https://doi.org/10.3390/app6100306.

AGREŽ, D. Weighted Multipoint Interpolated DFT to Improve Amplitude Estimation of Multifrequency Signal. IEEE Transactions on Instrumentation and Measurement, 2002, vol. 51, no. 2, p. 287-292. https://doi.org/10.1109/19.997826.

JACOBSEN, E. and KOOTSOOKOS, P. Fast, Accurate Frequency Estimators. IEEE Signal Processing Magazine, 2007, vol. 24, no. 3, p. 123-125. https://doi.org/10.1109/MSP.2007.361611.

CHEN, H., XU, F. an LI, J. A Frequency Estimator for Real Valued Sinusoidal Signals Using Three DFT Samples. In Proceedings of the 2018 International Conference on Radar (RADAR). Brisbane: IEEE, 2018. https://doi.org/10.1109/RADAR.2018.8557341.

Downloads

Published

07-09-2020

Issue

Section

Research Paper

Categories

How to Cite

Hájek, K. (2020). The Causes of Leakage Deviations from Sinc Function in DFT and Ways to Minimize Them. Advances in Military Technology, 15(2), 317-328. https://doi.org/10.3849/aimt.01375

Similar Articles

21-29 of 29

You may also start an advanced similarity search for this article.