Study of Astronomical and Geodetic Series using the Allan Variance

TL;DR

This paper reviews the use of Allan variance and its modifications for analyzing noise characteristics and stability in astronomical and geodetic time series data, highlighting its applications in understanding spectral and fractal noise structures.

Contribution

The paper introduces modifications to the classical Allan variance method for processing unevenly weighted and multidimensional data in astronomy and geodesy.

Findings

Effective noise analysis in astronomical and geodetic data

Modified AVAR handles unevenly weighted data

Insights into spectral and fractal noise structures

Abstract

Allan variance (AVAR) was first introduced more than 40 years ago as a estimator of the stability of frequency standards, and now it is actively used for investigations of time series in astronomy, geodesy and geodynamics. This method allows one to effectively explore the noise characteristics for various data, such as variations of station and source coordinates, etc. Moreover, this technique can be used to investigate the spectral and fractal structure of the noise in measured data. To process unevenly weighted and multidimensional data, which are usual for many astronomy and geodesy applications, AVAR modifications are proposed by the author. In this paper, a brief overview is given of using of classical and modified AVAR method in astronomy and geodynamics.