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首页> 外文期刊>IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control >Application of the Allan Variance to Time Series Analysis in Astrometry and Geodesy: A Review
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Application of the Allan Variance to Time Series Analysis in Astrometry and Geodesy: A Review

机译:Allan方差在占星术和大地测量学中的时间序列分析中的应用:综述

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The Allan variance (AVAR) was introduced 50 years ago as a statistical tool for assessing the frequency standards deviations. For the past decades, AVAR has increasingly been 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 clock measurements, is that they are generally associated with uncertainties; thus, an appropriate weighting should be applied during data analysis. In addition, some physically connected scalar time series naturally form series of multidimensional vectors. For example, three station coordinates time series , , and can be combined to analyze 3-D station position variations. The classical AVAR is not intended for processing unevenly weighted and/or multidimensional data. Therefore, AVAR modifications, namely weighted AVAR (WAVAR), multidimensional AVAR (MAVAR), and weighted multidimensional 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 astrogeodetic time series.
机译:艾伦方差(AVAR)是50年前引入的一种统计工具,用于评估频率标准偏差。在过去的几十年中,AVAR已越来越多地用于大地测量和天文测量中,以评估大地测量和天文测量时间序列中的噪声特征。与时钟测量相比,天文测量和大地测量的一个特定特征是它们通常与不确定性有关;因此,在数据分析过程中应使用适当的权重。另外,一些物理连接的标量时间序列自然形成多维向量的序列。例如,三个测站坐标时间序列,和可以组合以分析3-D测站位置变化。传统的AVAR不适用于处理加权不均匀和/或多维数据。因此,为了克服这些缺陷,引入了AVAR修改,即加权AVAR(WAVAR),多维AVAR(MAVAR)和加权多维AVAR(WMAVAR)。在本文中,简要回顾了使用AVAR的经验及其在处理大地测量时间序列中的修改。

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