[time-nuts] Characterising frequency standards

Steve Rooke sar10538 at gmail.com
Wed Apr 8 11:41:26 UTC 2009


Tom,

I understand fully the points that you have made but I have obviously
not made my point clear to all and i apologise for my poor
communication skills.

This is what I'm getting at:

Using your adev1.exe from http://www.leapsecond.com/tools/adev1.htm
and processing various forms of gps.dat from
http://www.leapsecond.com/pages/gpsdo-sim/gps.dat.gz.

C:\Documents and Settings\Steve Rooke\Desktop>adev1.exe 1 <gps.dat

** Sampling period: 1 s
** Phase data scale factor: 1.000e+000
** Total phase samples: 400000
** Normal and Overlapping Allan deviation:

       1 tau, 3.0127e-009 adev(n=399998),   3.0127e-009 oadev(n=399998)
       2 tau, 1.5110e-009 adev(n=199998),   1.5119e-009 oadev(n=399996)
       5 tau, 6.2107e-010 adev(n=79998),    6.1983e-010 oadev(n=399990)
      10 tau, 3.1578e-010 adev(n=39998),    3.1549e-010 oadev(n=399980)
      20 tau, 1.6531e-010 adev(n=19998),    1.6534e-010 oadev(n=399960)
      50 tau, 7.2513e-011 adev(n=7998),     7.3531e-011 oadev(n=399900)
     100 tau, 4.0029e-011 adev(n=3998),     4.0618e-011 oadev(n=399800)
     200 tau, 2.1512e-011 adev(n=1998),     2.1633e-011 oadev(n=399600)
     500 tau, 9.2193e-012 adev(n=798),      9.1630e-012 oadev(n=399000)
    1000 tau, 4.9719e-012 adev(n=398),      4.7750e-012 oadev(n=398000)
    2000 tau, 2.6742e-012 adev(n=198),      2.5214e-012 oadev(n=396000)
    5000 tau, 1.0010e-012 adev(n=78),       1.1032e-012 oadev(n=390000)
   10000 tau, 6.1333e-013 adev(n=38),       6.1039e-013 oadev(n=380000)
   20000 tau, 3.8162e-013 adev(n=18),       3.2913e-013 oadev(n=360000)
   50000 tau, 1.0228e-013 adev(n=6),        1.5074e-013 oadev(n=300000)
  100000 tau, 5.8577e-014 adev(n=2),        6.7597e-014 oadev(n=200000)

So far, so good. Now I delete every even line in the file which leaves
me with 200000 lines of data (400000 lines in original gps.dat file).
(awk 'and(NR, 1) == 0 {print}' <gps.dat >gps1.dat)

C:\Documents and Settings\Steve Rooke\Desktop>adev1.exe 1 <gps1.dat

** Sampling period: 1 s
** Phase data scale factor: 1.000e+000
** Total phase samples: 200000
** Normal and Overlapping Allan deviation:

       1 tau, 3.0257e-009 adev(n=199998),   3.0257e-009 oadev(n=199998)
       2 tau, 1.5373e-009 adev(n=99998),    1.5345e-009 oadev(n=199996)
       5 tau, 6.3147e-010 adev(n=39998),    6.3057e-010 oadev(n=199990)
      10 tau, 3.3140e-010 adev(n=19998),    3.3067e-010 oadev(n=199980)
      20 tau, 1.7872e-010 adev(n=9998),     1.7810e-010 oadev(n=199960)
      50 tau, 7.9428e-011 adev(n=3998),     8.1216e-011 oadev(n=199900)
     100 tau, 4.2352e-011 adev(n=1998),     4.3265e-011 oadev(n=199800)
     200 tau, 2.2001e-011 adev(n=998),      2.2593e-011 oadev(n=199600)
     500 tau, 9.6853e-012 adev(n=398),      9.5441e-012 oadev(n=199000)
    1000 tau, 5.0139e-012 adev(n=198),      5.0387e-012 oadev(n=198000)
    2000 tau, 2.7994e-012 adev(n=98),       2.7090e-012 oadev(n=196000)
    5000 tau, 1.4280e-012 adev(n=38),       1.2214e-012 oadev(n=190000)
   10000 tau, 7.4881e-013 adev(n=18),       6.5814e-013 oadev(n=180000)
   20000 tau, 7.6518e-013 adev(n=8),        3.7253e-013 oadev(n=160000)
   50000 tau, 2.4698e-014 adev(n=2),        1.3539e-013 oadev(n=100000)

Obviously we don't have enough data now for a measurement of 100000
tau but the results for the other tau are quite close, especially when
there are sufficient data points. Now this is discontinuous data,
exactly what I was trying to allude to.

OK, so now I take only the top 200000 lines of the gps.dat file (head
-200000 gps.dat >gps2.dat)

C:\Documents and Settings\Steve Rooke\Desktop>adev1.exe 1 <gps2.dat

** Sampling period: 1 s
** Phase data scale factor: 1.000e+000
** Total phase samples: 200000
** Normal and Overlapping Allan deviation:

       1 tau, 3.0411e-009 adev(n=199998),   3.0411e-009 oadev(n=199998)
       2 tau, 1.4985e-009 adev(n=99998),    1.4999e-009 oadev(n=199996)
       5 tau, 6.1964e-010 adev(n=39998),    6.2010e-010 oadev(n=199990)
      10 tau, 3.1315e-010 adev(n=19998),    3.1339e-010 oadev(n=199980)
      20 tau, 1.6499e-010 adev(n=9998),     1.6495e-010 oadev(n=199960)
      50 tau, 7.1425e-011 adev(n=3998),     7.3416e-011 oadev(n=199900)
     100 tau, 3.9940e-011 adev(n=1998),     4.0730e-011 oadev(n=199800)
     200 tau, 2.1488e-011 adev(n=998),      2.1558e-011 oadev(n=199600)
     500 tau, 8.4809e-012 adev(n=398),      9.0886e-012 oadev(n=199000)
    1000 tau, 4.9223e-012 adev(n=198),      4.7104e-012 oadev(n=198000)
    2000 tau, 2.4335e-012 adev(n=98),       2.4515e-012 oadev(n=196000)
    5000 tau, 1.0308e-012 adev(n=38),       1.0861e-012 oadev(n=190000)
   10000 tau, 5.9504e-013 adev(n=18),       6.1031e-013 oadev(n=180000)
   20000 tau, 3.6277e-013 adev(n=8),        3.1994e-013 oadev(n=160000)
   50000 tau, 1.0630e-013 adev(n=2),        1.6715e-013 oadev(n=100000)

Is there any Linux tools for calculating adev as I'm having to run
Windows in a VMware session?

73,
Steve

2009/4/8 Tom Van Baak <tvb at leapsecond.com>:
> Steve,
>
> You've asked a couple of questions. Let me start with this.
>
> It is true that if one were only interested in the performance
> of a pendulum (or quartz or atomic) clock for averaging times
> of one day that all you would need is a series of time error
> (aka phase) measurements made about the same time once
> a day (doesn't have to be that exact). After one week, you'd
> have 7 error measurements (=6 frequency =5 stability points)
> and this is adequate to calculate the ADEV for tau 1 day.
> This alone allows you to rank your clock among all the other
> pendulum clocks out there. Note also you get time error and
> rate error from these few data points too.
>
> As another example, suppose you have a nice HP 10811A
> oscillator and want to measure its drift rate. In this case you
> could spend just 100 seconds and measure its frequency
> once a day, or even once every couple of days. Do this for
> a month and you'd have several dozen points. If you plot
> these frequency measurements you will likely see that they
> approximately fall on a line; the slope of the is the frequency
> drift rate of the 10811. The general shape of the points, or
> the fit of the line is a rough indication of how consistent the
> drift rate is or if it's increasing or decreasing.
>
> Neither of these examples require a lot of data. Both of these
> are real-world examples.
>
> OK so far?
>
> /tvb
>
>
>
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>



-- 
Steve Rooke - ZL3TUV & G8KVD & JAKDTTNW
Omnium finis imminet



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