Precision estimation and forecasting of the earth’s orientation parameters with the singular spectrum analysis method

Choliy, V. Ya.

doi:10.3103/s0884591315040030

Cited by 3 publications

(1 citation statement)

References 2 publications

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“…Helmert transform (HT) and singular spectrum analysis (SSA) in one-dimension variant were used by author and his colleagues in their works [1,2,3,4,5].…”

Section: Introductionmentioning

confidence: 99%

Formal estimation of the random component in global maps of total electron content

Choliy

2016

Adv.Astron.Spa.Physics

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“…Helmert transform (HT) and singular spectrum analysis (SSA) in one-dimension variant were used by author and his colleagues in their works [1,2,3,4,5].…”

Section: Introductionmentioning

confidence: 99%

Formal estimation of the random component in global maps of total electron content

Choliy

2016

Adv.Astron.Spa.Physics

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Investigation of time_changeable seasonal components in the GPS height time series: A case study for Central Europe

Gruszczyńska¹

2016

Acta Geodynamica Et Geomaterialia

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Nowadays, beyond the dispute we should take into account the time-varying parameters of seasonals in the GPS-derived position time series. Either real geophysical effects or systemspecified artefacts can introduce non-sinusoidal changes. For this study, we used 18 daily position time series from Central European stations provided by the Jet Propulsion Laboratory (JPL) processed in the GIPSY-OASIS software in a Precise Point Positioning (PPP) mode. We tested two different approaches to subtract the seasonal signals: Least-Squares Estimation (LSE) and Singular Spectrum Analysis (SSA). The SSA approach is suitable for all (stationary and nonstationary) time series, without prior knowledge about the data characteristics, which is an undisputable advantage. We extracted periodicities from GPS position time series, and demonstrated the usefulness of the SSA approach on the example of the vertical component. We showed, that the reassembled signal, containing only the first four Reconstructed Components, has a larger correlation coefficient than LSE-extracted signals, with respect to the original time series. Moreover, using the Akaike Information Criterion and Fisher-Snedecor test we tested optimum length of the sliding window and significance of the obtained RCs, respectively. ARTICLE INFO

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On the usage of the Singular Spectrum Analysis for precision estimation and editing of total atmospheric delay time series

Vasiuta¹,

Choliy²

2016

Adv.Astron.Spa.Physics

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We use Singular Spectrum Analysis (SSA) for precision estimation of time series of total zenith atmospheric delay for a list of European GNSS data stations proceed in Main Astronomical Observatory GNSS processing centre. The series are downloadable at ftp://ftp.mao.kiev.ua/pub/gnss/products/IGS05/. Analysis of the principal components of the series allowed us to clean the series by removing noise out of them. With the capabilities of SSA some gaps in the data were filled out.

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Precision estimation and forecasting of the earth’s orientation parameters with the singular spectrum analysis method

Cited by 3 publications

References 2 publications

Formal estimation of the random component in global maps of total electron content

Formal estimation of the random component in global maps of total electron content

Investigation of time_changeable seasonal components in the GPS height time series: A case study for Central Europe

On the usage of the Singular Spectrum Analysis for precision estimation and editing of total atmospheric delay time series

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