Comprehensive Manual114
© 2018 Nortek AS
dependent largely on the quality of the dataset. Histograms are actually extremely useful for this
type of work. A lot of times the ambiguity velocity causes the tail of a histogram to be cut off and
shifted to the wrong side of the histogram (so, a sign filter would probably work wonder here)
meaning visually it is fairly easy to pick out wrapped velocities. At the least, this is a good way to
check the success of any identification scheme developed
To unwrap the data: It is, in principle, possible to unwrap data when you can make assumptions
about du/dt but only if the SNR and correlation is good.There are two ways to go about dealing with
your present data.
1. Develop an outlier filter to remove the wrapped data. If there are only a few points (some small
percentage of the total data) it's relatively simple to define a cutoff threshold outside of which you
discard the velocity data. If needed, you can interpolate these removed points back in as long as the
gaps created by removing them are not too large. The advantage of this is it is relatively simple and
quick, and the impact on statistics is going to be fairly minimal because so few points are involved.
2. If the number of wrapped points is fairly high, the above is problematic because the variance of the
signal is artificially constrained by the phase wrapping (i.e. the largest events are being eliminated
from sampling). In this case the data either needs to be corrected or retaken. For a field deployment
this generally means correction. Below are the recommended steps for going about this.
Step 1 in ambiguity correction is to get the data back into beam coordinates. Search for "Coordinate
Transformation" in our FAQ database to find an explanation on how to do this, or confer our Practical
Primer for Pulse Coherent Instruments available under Documents.
Step 2 is to find the Ambiguity Velocity. Ambiguity Velocity (the velocity corresponding to pi,
denoted V_amb) is the maximum beam velocity which can be measured by the instrument in its
deployed configuration. This is set by the Nominal Velocity Range in the configuration window of the
software. There are two ways of finding this velocity:
A simple estimate of Vamb is the average of the absolute values of the maximum and minimum
measured velocities.
A more accurate expression is V_amb = c / ( 4 * f * timeLagInSeconds ), where c is the speed of
sound, f is the instrument frequency and timeLagInSeconds is pulled from the configuration
information in the *.HDR file. (this formula is the standard Pulse Coherent maximum velocity
calculation. Search for "lag" in our FAQ database to read more about this).
Step 3 is to remove the Vamb. The procedure is like this:
loop over all the data points
If large jump in velocity, then
if the jump is negative, then
newvel = oldvel + 2*Vamb
else
newvel = oldvel - 2*Vamb
end
end
end loop
Step 4 is to transform the velocities back to XYZ or ENU
A few words of caution. It is generally best to avoid phase wrapping issues as the time spent
correcting them is often fairly significant. The most difficult task is identifying the points which are
wrapped and automating this process. The correction is fairly simple once points are identified
however.
5.3.8 Mooring/mounting Vibrations
Excessive mooring vibration can adversely affect the data. Vibration introduces spurious velocities
and interferes with the proper operation of the tilt sensor. You may be able to detect intervals of
excessive vibration by looking closely at the data. If you discover that mooring vibration is a problem,
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