John,
On 02/10/2012 12:37 AM, John Miles wrote:
Indeed, ADEV is for random freq variation not easily measured by other
means.
Well, no, ADEV is the two-sample deviation of fractional frequency
differences over time. That's really all you can say about it. There's not
really any such thing as "true ADEV" -- a measurement either meets the
mathematical criteria for Allan deviation, or it doesn't.
Well, does the ADEV of a systematic temperature dependence or drift
property give you any meaningful values, or is ADEV the only answer to
your question?
My point is that ADEV and TDEV just doesn't give very useful information
on your oscillators behaviours for systematic effects, but ADEV and TDEV
can give you more information on your random noise sources contribution
if you remove the parts being obscured by the systematic effects.
The various systematic effects is best handled with other tools, and
then when we have established meaningful values of a suitable model, we
can then apply the model to the stress-cases of our choosing and get
meaningful results out of that, which is usually what you want to do.
Temperature fluctuations do not cause random freq changes and the
temperature's effect should be removed if one wants accurate long term
ADEV numbers.
No, accurate ADEV numbers are whatever you see on an accurate ADEV plot. :)
Whatever an accurate ADEV plot is, means and indeed is attainable at
all. There is no true accurate ADEV plot, it's full of compromises,
side-effects and stuff.
If I measure two sources in the same environment and I see HVAC ripple on
one ADEV trace but not on the other, then that may be useful information, or
even the only information I care about. (Of course, it's only useful if
the bin density is high enough to show the effect in question, but that's
not the fault of the ADEV metric itself.)
ADEV isn't the only tool to see that, it may not even be the best tool
to analyze it.
If you don't want to observe the effect of temperature fluctuations on your
DUT, random or otherwise, the correct solution is not to use a different
metric or to tweak the data, but to shield the DUT against the temperature
variations in question.
Easier said than done. ADEV just isn't the one and only tool to use.
Even daily diurnal cycles due to temperature can have major negative
effect
on ADEV numbers as low as 2000 to 3000 seconds,
Your bin density may be insufficient in that case. ADEV is not unlike an
FFT in that regard -- the denser the bins, the higher the resolution,
subject to limitations imposed by the window transfer function. (Enrico
Rubiola has suggested that we should have been using FFT-like measures for
long term stability all along, instead of ADEV.)
There are also a huge number of ADEV estimator methods, crunching out
different precision in their estimation of ADEV. FFT is one possible
method alongside some processing that has been proposed.
It's true that the ADEV function is not all that sharp, but you shouldn't
ordinarily see effects removed from their causes by a 40:1 tau ratio. IMHO,
if you are seeing significant degradation at the 2000-second level caused by
diurnal cycles at the 12-hour level, something may be wrong.
Outliers are another matter, due to the infinite "ringing" that a step
function causes. They should be removed from ADEV and considered as a
separate source of error. Transients cause some pretty horrible effects in
FFTs as well, regardless of the window characteristics. Offhand, I can't
think of any simple frequency-stability metrics that are good at ignoring
outliers, and I'm not sure it'd be a good thing if we were to invent one.
What is a step or spike in time becomes a resonance in the frequency domain.
What is a step or spike in the frequency domain becomes a resonance in
the time domain.
ADEV is a kind of frequency domain tool.
and if there is an Heater or AC cycling, then any ADEV numbers about a few
hundred seconds can be due to TempCoeff, which should not be measured
with ADEV or included in ADEV plots.
Again, fractional frequency differences are fractional frequency
differences. ADEV will show temperature effects, as will an FFT or most
other metrics worth using. If you don't want to see these effects, you need
to take the appropriate measures to fix the environment, the DUT, the
instrumentation, or all of the above.
This is much the same as a single outlier data point that can screw up the
whole ADEV plot and make it pretty much meaningless and unrepeatable.
Ditto for linear ageing, Should be remove first if one wants true ADEV
plots.
Linear drift is a good thing to take out... *if* you explicitly want to
exclude it from your observation of fractional frequency-difference
statistics. Maybe you consider drift or aging to be a valid part of the
statistics you're collecting. If so, leave it in. Maybe you plan to
discipline the DUT in a way that will remove drift and aging. If so, remove
it. You're going to get a "valid" measurement of ADEV either way... but
determining whether ADEV is really the best metric to use, and interpreting
it in light of your application, is always up to you.
Linear drift will be scaled correctly. When setting confidence bounds
the systematic effect confidence bounds will not match up with the
confidence bounds of the random statistics, so you will get fooled,
besides the bias aspect.
ADEV as a tool was meant to handle random noises, but not the systematic
noise. When doing engineering estimates ADEV or TDEV with suitable
scale-ups then adds to the systematic effects. They need to be treated
as time treats them in different ways.
It's clear we don't see our ADEVs the same way.
Cheers,
Magnus
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