Surrogate data generation technology using the SSA method for enhancing the effectiveness of signal spectral analysis

Authors

DOI:

https://doi.org/10.3103/S0735272715080038

Keywords:

surrogate data, surrogate noise, singular spectrum analysis method, SSA, Root-MUSIC method

Abstract

The problem of enhancing the effectiveness of spectral analysis of signals observed against the background of noise has been considered by using the Root-MUSIC method and the surrogate data technology that is free from surrogate noise. The surrogate data was obtained by using the singular spectrum analysis method (SSA). The application of this technology was shown to be effective in the range of both small and large signal-to-noise ratios when the frequencies of signal components are a multiple of the observation sampling frequency.

References

STOICA, P.; MOSES, R.L. Introduction to Spectral Analysis. Prentice-Hall, 1997.

VASYLYSHYN, V.I. High-resolution phased array signal processing via DFT beamspace TLS-ESPRIT with structure weighting. Proc. of IEEE Int. Symp. on Phased Array Systems and Technology, 14-17 Oct. 2003, Boston, Massachusetts, USA. IEEE, 2003, p.605-610, DOI: http://dx.doi.org/10.1109/PAST.2003.1257049.

LEKHOVYTSKIY, D.I.; RAKOV, I.D. The efficiency of adaptive spatial processing of signals in the process of time correlation of learning samples. Radiotekhnika, 1986, n.9, p.60-63.

VASYLYSHYN, V.I. Adaptive variant of the surrogate data technology for enhancing the effectiveness of signal spectral analysis using eigenstructure methods. Izv. Vyssh. Uchebn. Zaved., Radioelektron., 2015, v.58, n.3, p.26-39 [Radioelectron. Commun. Syst., 2015, v.58, n.3, p.116-126, DOI: http://dx.doi.org/10.3103/S0735272715030036].

EFRON, B. Nonconventional Methods of Multivariate Statistical Analysis. Moscow: Finansy i Statistika, 1988 [in Russian, translation from English of articles collection], 263 p.

VASYLYSHYN, V. Removing the outliers in root-MUSIC via pseudo-noise resampling and conventional beamformer. Signal Processing, 2013, v.93, n.12, p.3423-3429, DOI: http://dx.doi.org/10.1016/j.sigpro.2013.05.026.

THEILER, JAMES S.; EUBANK, STEPHEN; LONGTIN, ANDRE; GALDRIKIAN, BRYAN; FARMER, J. DOYNE. Testing for nonlinearity in time series: the method of surrogate data. Physica D, Sept. 1992, v.58, n.1-4, p.77, PII: 016727899290102S.

KOSTENKO, P.Y.; VASYLYSHYN, V.I. Enhancing the efficiency of spectral analysis of signals by the Root-MUSIC method using surrogate data. Izv. Vyssh. Uchebn. Zaved., Radioelektron., 2014, v.57, n.1, p.31-39 [Radioelectron. Commun. Syst., 2014, v.57, n.1, p.31-38, DOI: http://dx.doi.org/10.3103/S0735272714010026].

KOSTENKO, P.Y.; VASYLYSHYN, V.I. Signal processing correction in spectral analysis using the surrogate autocovariance observation functions obtained by the ATS-algorithm. Izv. Vyssh. Uchebn. Zaved., Radioelektron., 2014, v.57, n.6, p.3-12 [Radioelectron. Commun. Syst., 2014, v.57, n.6, p.235-243, DOI: http://dx.doi.org/10.3103/S0735272714060016].

VASYLYSHYN, V.I. Enhancing the spectral analysis efficiency by eigenstructure methods using the surrogate data technology for eigenvectors of the covariance observation matrix. Radiotekhnika (Kharkiv), 2013, n.174, p.66-72.

KOSTENKO, P.Y.; VASYLYSHYN, V.I. Enhancing the spectral analysis efficiency at low signal-to-noise ratios using the technology of surrogate data without the segmentation of observation. Izv. Vyssh. Uchebn. Zaved., Radioelektron., 2015, v.58, n.2, p.36-47 [Radioelectron. Commun. Syst., 2015, v.58, n.2, p.75-84, DOI: http://dx.doi.org/10.3103/S0735272715020041].

ALEXANDROV, F.I.; GOLYANDINA, N.E. The automatic extraction of time series trend and periodical components with the help of the Caterpillar-SSA approach. Exponenta Pro, 2004, n.3-4, p.54-61.

DERGUNOV, A.V.; KUTS, Y.V.; SHCHERBAK, L.M. Proc. of Third Microwaves, Radar and Remote Sensing Symp., 2011, Kyiv, Ukraine. Kyiv, 2011, p.378-381.

VASYLYSHYN, V.I. Preliminary signal processing using the SSA method in spectral analysis problems. Prikladnaya Radioelektronika, 2014, v.13, n.1, p.42-49.

Published

2015-08-16

Issue

Section

Research Articles