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首页> 外文期刊>IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control >The total deviation approach to long-term characterization offrequency stability
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The total deviation approach to long-term characterization offrequency stability

机译:用总偏差法长期表征频率稳定性

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摘要

Total variance represents the first advancement in the estimationnof an oscillating signal's long-term frequency stability since thenconventional Allan variance estimator. It is called “Totvar”n(pronounced tot-var) for short. Its commonly reported square-root is thentotal deviation function called “Totdev” (tot-dev). Totdevnefficiently extracts broadband FM oscillator noise levels and typesncommonly encountered at long-term Τ-averaging times, even thoughnthese are difficult to measure. The notable advantages of Totdevninclude: significantly improved confidence for estimating long-termnfrequency stability, lower sensitivity to the removal of linearnfrequency drift, and exact decomposition of the sample variance ofnfrequency residuals. A review of some methods of improving thenestimation of long-term stability is presented. Concepts of datanextrapolation and smoothing are developed and linked to the definitionnof Totdev. The approach to interpreting a Σ vs. Τ stabilitynplot of Totdev is given and is identical to that using the Allanndeviation. Formulas are given for computing confidence interval at longnterm and for computing an easily removed, slight negative bias. The lastnsection shows how Totdev is the first frequency-stability statistic thatnis unified to the more readily understood, but often inappropriate,nstandard deviation by an exact decomposition
机译:总方差代表了自传统的Allan方差估计器以来,在振荡信号的长期频率稳定性估计中的第一个进步。简称为“ Totvar” n(发音为tot-var)。然后,它通常报告的平方根就是称为“ Totdev”(tot-dev)的总偏差函数。即使很难测量,Totdev仍无法有效地提取出在长时间Τ平均时通常遇到的宽带FM振荡器噪声电平和类型。 Totdevn的显着优势包括:显着提高了估计长期频率稳定性的置信度,降低了线性频率漂移消除的灵敏度以及精确分解了n频率残差的样本方差。提出了一些改善长期稳定性的方法的综述。开发了数据外推和平滑的概念并将其链接到Totdev的定义。给出了解释Totdev的Σvs T稳定性图的方法,该方法与使用Allanndeviation的方法相同。给出了用于长期计算置信区间和计算易于去除的轻微负偏差的公式。最后一部分显示了Totdev是第一个频率稳定性统计量,它通过精确分解统一为更容易理解但通常不适当的标准偏差

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