13.07.2015 Views

NIST Technical Note 1337: Characterization of Clocks and Oscillators

NIST Technical Note 1337: Characterization of Clocks and Oscillators

NIST Technical Note 1337: Characterization of Clocks and Oscillators

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where c = Dr/2. In regression analysis, it is customary to use the symbol "y"as the dependent variable <strong>and</strong> "X" as the independent variable. This is in conflictwith usage in time <strong>and</strong> frequency where "X" <strong>and</strong> "y" (time error <strong>and</strong> frequencyerror, respectively) are dependent on a coarse measure <strong>of</strong> time, t, theindependent variable. This paper will follow the time <strong>and</strong> frequency custom eventhough this may cause Some confusion in the use <strong>of</strong> regression analysis text books.The model given by Eq. 2 is complete if the r<strong>and</strong>om component, ~(t), is a whitenoise (i.e., r<strong>and</strong>om, uncorrelated, normally distributed, zero mean, <strong>and</strong> finitevariance).III. EXAMPLEOne must emphasize here that ALL results regarding parameter error magnitudes<strong>and</strong> their distributions are totally dependent on the adequacy <strong>of</strong> the model. Aprimary source <strong>of</strong> errors is <strong>of</strong>ten autocorrelation <strong>of</strong> the residuals (contrary tothe explicit model assumptions). While simple visual inspection <strong>of</strong> the residualsis <strong>of</strong>ten sufficient to recognize the autocorrelation problem, "whitenesstests" can be more objective <strong>and</strong> precise.This section analyzes a set <strong>of</strong> 94 hourly values <strong>of</strong> the time difference betweentwo oscillators. Figure 1 is a plot <strong>of</strong> the time difference (measured in microseconds)between the two oscillators. The general curve <strong>of</strong> the data along withthe general expectation <strong>of</strong> frequency drift in crystal oscillators leads one totry the quadratic behavior (Model #1; models #2 <strong>and</strong> #3 discussed below). Whileit is not common to find white phase noise on oscillators at levels indicated onthe plot, that assumption will be made temporarily. The results <strong>of</strong> the regressionare summarized in a conventional Analysis <strong>of</strong> Variance, Table 2.TABLE 2.ANALYSIS OF VARIANCE QUADRATIC FIT TO PHASE(Units: seconds squared)SOURCE SUM OF SQUARES d.f. MEAN SQUARERegression 2.32E-9 3Residuals 4.26E-12 91 4.68E-14Total 2.329E-9 94 2.48E-11Coefficient <strong>of</strong> simple determination 0.99713Parameters:AaAbAc1.10795E-5 (seconds) t-ratio 161.98= 1.4034E-10 (sec/sec) t-ratio 152.02= -3.7534E-16 (sec/sec2) t-ratio -143.51553IN-266

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