Improving the performance of spectral analysis with preliminary signal processing by SSA method in the conditions of threshold signal-to-noise ratio

Main Article Content

Volodymyr Vasylyshyn
https://orcid.org/0000-0002-5461-0125
Victor Lyutov
https://orcid.org/0000-0001-8092-5748
Dmytro Komin
https://orcid.org/0000-0003-4439-346X

Abstract

The subject of the paper is the methods of spectral analysis, singular spectrum analysis method. The purpose of this paper is improving the performance of spectral analysis (reduction of the value of root mean square error of frequency estimation) in the condition of threshold signal-to-noise ratio (SNR) when using preliminary signal processing by SSA method. Results. Based on the author’s previously developed method of spatial spectral analysis based on joint using the several methods of spectral analysis and preliminary signal processing with using modified SSA the calculation of SSA in the case of threshold SNR is proposed. Furthermore, it is not necessary to calculate the SSA in the condition of medium and high SNR. This simplification can be explained by the fact that in such conditions the performance of the modern methods of spectral analysis is high. Conclusions. The conducted investigation shows that using the proposed approach in the case of threshold SNR allows obtaining the accuracy of frequency estimation of harmonic components of the signal which is provided in the case of application of the SSA method. In the case of high and medium SNRs the accuracy is determined by accuracy of the method of spectral analysis. The obtained results can be used for the communication channel state estimation and direction of arrival estimation of radiation source.

Article Details

How to Cite
Vasylyshyn, V., Lyutov, V., & Komin, D. (2019). Improving the performance of spectral analysis with preliminary signal processing by SSA method in the conditions of threshold signal-to-noise ratio. Advanced Information Systems, 3(2), 69–72. https://doi.org/10.20998/2522-9052.2019.2.12
Section
Information systems research
Author Biographies

Volodymyr Vasylyshyn, Ivan Kozhedub Kharkiv National Air Force University, Kharkiv

Doctor of Technical Science, Associate Professor, Head of Department

Victor Lyutov, Ivan Kozhedub Kharkiv National Air Force University, Kharkiv

PhD student

Dmytro Komin, Ivan Kozhedub Kharkiv National Air Force University, Kharkiv

Candidate of Technical Sciences, Senior Teacher of Department

References

Marple, S.L. (2018), Digital Spectral Analysis, Second Edition. Dover Publication Inc, Maniola New York, 420 p.

Golyandina, N., and Zhigljavsky, A (2013), Singular spectrum analysis for time series, Springer, London, 120 p.

Sanei, S., Hassani, H. (2016), Singular Spectrum Analysis of Biomedical Signals, CRC Press, London, 260 p.

Dahlhaus, R., Kurths, J., Maass, P., Timmer, J (2008), Mathematical Methods in Signal Processing and Digital Image Analy-sis, Springer-Verlag, Berlin Heidelberg, 293 p.

Lancaster, G., Iatsenko, D., Pidde, A., Ticcinelli, V. and Stefanovska, A. (2018), “Surrogate data for hypothesis testing of physical systems”, Physics Reports, Vol. 748, pp. 1–60.

Vasylyshyn, V. (2013), “Removing the outliers in root–MUSIC via pseudo–noise resampling and conventional beamformer”, Signal processing. Vol. 93, pp. 34.23–34.29.

Kostenko, P.Yu. and Vasylyshyn, V.I. (2015), “Surrogate data generation technology using the SSA method for enhancing the effectiveness of signal spectral analysis”, Radioelectronics and Communication System, Vol. 58, pp. 356–361.

Vasylyshyn, V. and Lyutov, V. (2018), “Signal denoising using modified complex SSA method with application to frequency estimation.”, 5th International Scientific-Practical Conference Problems of Infocommunications, Science and Technology, Proc. Int. Conf., October 9-12, 2018, Kharkiv, pp.715–718.