Application of the Allan Variance to Time Series Analysis in Astrometry and Geodesy: A Review

Fuente: arXiv
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Autor principal: Malkin, Zinovy
Formato: Preprint
Publicado: 2016
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author Malkin, Zinovy
author_facet Malkin, Zinovy
contents The Allan variance (AVAR) was introduced 50 years ago as a statistical tool for assessing of the frequency standards deviations. For the past decades, AVAR has increasingly being used in geodesy and astrometry to assess the noise characteristics in geodetic and astrometric time series. A specific feature of astrometric and geodetic measurements, as compared with the clock measurements, is that they are generally associated with uncertainties; thus, an appropriate weighting should be applied during data analysis. Besides, some physically connected scalar time series naturally form series of multi-dimensional vectors. For example, three station coordinates time series $X$, $Y$, and $Z$ can be combined to analyze 3D station position variations. The classical AVAR is not intended for processing unevenly weighted and/or multi-dimensional data. Therefore, AVAR modifications, namely weighted AVAR (WAVAR), multi-dimensional AVAR (MAVAR), and weighted multi-dimensional AVAR (WMAVAR), were introduced to overcome these deficiencies. In this paper, a brief review is given of the experience of using AVAR and its modifications in processing astro-geodetic time series.
format Preprint
id arxiv_https___arxiv_org_abs_1607_04712
institution arXiv
publishDate 2016
record_format arxiv
spellingShingle Application of the Allan Variance to Time Series Analysis in Astrometry and Geodesy: A Review
Malkin, Zinovy
Instrumentation and Methods for Astrophysics
Data Analysis, Statistics and Probability
Geophysics
The Allan variance (AVAR) was introduced 50 years ago as a statistical tool for assessing of the frequency standards deviations. For the past decades, AVAR has increasingly being used in geodesy and astrometry to assess the noise characteristics in geodetic and astrometric time series. A specific feature of astrometric and geodetic measurements, as compared with the clock measurements, is that they are generally associated with uncertainties; thus, an appropriate weighting should be applied during data analysis. Besides, some physically connected scalar time series naturally form series of multi-dimensional vectors. For example, three station coordinates time series $X$, $Y$, and $Z$ can be combined to analyze 3D station position variations. The classical AVAR is not intended for processing unevenly weighted and/or multi-dimensional data. Therefore, AVAR modifications, namely weighted AVAR (WAVAR), multi-dimensional AVAR (MAVAR), and weighted multi-dimensional AVAR (WMAVAR), were introduced to overcome these deficiencies. In this paper, a brief review is given of the experience of using AVAR and its modifications in processing astro-geodetic time series.
title Application of the Allan Variance to Time Series Analysis in Astrometry and Geodesy: A Review
topic Instrumentation and Methods for Astrophysics
Data Analysis, Statistics and Probability
Geophysics
url https://arxiv.org/abs/1607.04712