L.V. Grunskaya - Dr. Sc. (Eng.), Professor, Associate Professor, Department of General and Applied Physics, Vladimir State University named after A.&N. Stoletovs. E-mail: grunsk@vlsu.ru V.V. Isakevich - Ph. D. (Eng.), Senior Research Scientist, Department of General and Applied Physics, Vladimir State University named after A.&N. Stoletovs. E-mail: businesssoftservice@gmail.com D.V. Isakevich - Research Engineer, Department of General and Applied Physics, Vladimir State University named after A.&N. Stoletovs. E-mail: voiceofhope@yandex.ru V.E. Lukyanov - Post-graduate Student, Department of General and Applied Physics, Vladimir State University named after A.&N. Stoletovs. E-mail: slayer@mail.ru

The article demonstrates the advantages of using eigenoscope (Grunskaya L.V, Isakevitch V.V., Isakevitch D.V. RF patent № 116242 of 30.09.2011) for detecting non-coherent complex-periodic components of the vertical electric field Ez time series in the Earth atmosphere boundary layer, localized at combined lunar tide frequencies. The incoherence of these components makes them undetectable by means of conventional schemes of spectral analysis since, as it has been proved by long term observation, the increase of the analysis time-range leads to a monotone decrease of spectral estimates. Unlike the conventional spectral analysis, eigenoscopy is based on analysing signal eigenvectors, which themselves contain the infor-mation of the analysed time series structure. In other words, if time series has spectrally localized components, its eigenvectors will also contain those components. Representing time series in eigenvectors basis takes the least number of components, i.e. has the maximum expressiveness. So, spectral analysis of eigenvectors has higher sensitivity than the conventional spectral analysis of time series. Using eigenoscopy makes it possible to detect non-coherent and non-dominant energetically components, spectrally localized at considered frequencies. Basically eigenoscope consists of four blocks. The analysed time-series is the input of the scaling block. The next block calculates the covariance matrix (CV) of the time-series for the given analysis range. The CV is supplied to the input of the block for calculating ei-genvectors and eigenvalues. The last block performs the analysis of eigenvectors and eigenvalues in order to detect the characteristic signs of the sought physical phenomena and assessing their parameters. The detection of components spectrally localized at combined frequencies makes it possible to use these components as additional means of getting information about geophysical and astrophysical processes. The work is carried out with the support of State Assignment 2014/13,2871 and RFRF Grant № 14-07-97510\\14. Calculations were made using free software GNU Octave, CeCILL Scilab, GNU G95.

 

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