Allan variances and its related methods are commonly used to analyse a sequence of data in the time domain to measure frequency stability of oscillators. It allows for a determination of noise type as a function of the averaging time. This method is one of the most popular for identifying different noise types in the sensors data, and it is usually used for a wide range of studies on the stability of oscillators or atomic clocks. In this paper, the authors propose their own algorithm for a qualitative and quantitative expression of noise type using Allan and related variation. The methods currently used allow for the determination of the noise type graphically only, without quantifying the type and percentages for each of the integration steps. Our study allows for a numerical interpretation of the Allan (and related) variances data. A numerical example of the described method is based on GPS satellite clock corrections for 1825–2086 GPS Week (5 years) based on daily 30-s sampling interval products.

中文翻译：

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一种定量和定性表示艾伦（及相关）方差中噪声类型的新方法

艾伦方差及其相关方法通常用于分析时域中的数据序列，以测量振荡器的频率稳定性。它允许确定作为平均时间函数的噪声类型。这种方法是最流行的识别传感器数据中不同噪声类型的方法之一，通常用于对振荡器或原子钟稳定性的广泛研究。在本文中，作者提出了他们自己的算法，用于使用 Allan 和相关变化对噪声类型进行定性和定量表达。当前使用的方法仅允许以图形方式确定噪声类型，而不量化每个积分步骤的类型和百分比。我们的研究允许对艾伦（和相关）方差数据进行数值解释。