0
$\begingroup$

I am using the following code to generate an allen variance plot from some accelerometer data

https://github.com/nmayorov/allan-variance/blob/master/allan_variance.py

It seems a sound implementation looking at Allan variance definitions I can find online

How do I interpret this graph?

![enter image description here

Improve this question
$\endgroup$

1 Answer 1

Reset to default
1
$\begingroup$

This is the result of drift (non-stationary data). The horizontal axis is the averaging time $\tau$, and the vertical axis is the standard deviation (ADEV) of differences between successive blocks of data each $\tau$ long, and separated by $\tau$ seconds. If the data had a stationary white noise statistic, the ADEV would instead be going down at the square root of tau. For more on ADEV please see these posts:

Bias instability in Gyroscopes : AVER / ADEV

How to interpret Allan Deviation plot for gyroscope?

Is Allan variance still relevant?

Improve this answer
$\endgroup$
2
  • $\begingroup$ indeed, my data was not stationary. I guess I should look again at this plot after taking first temporal difference of the data to make them stationary? when doing that, indeed the slope changes to negative $\endgroup$
    – 00__00__00
    Dec 8, 2022 at 7:26
  • $\begingroup$ That is what the ADEV computation does.. .the point is that gyroscopes drift and are not stationary. The ADEV is very useful to quantify and compare non-stationary processes since it will do that difference you describe, so you don't need to do that first. $\endgroup$
    – Dan Boschen
    Dec 8, 2022 at 14:51

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge that you have read and understand our privacy policy and code of conduct.

Not the answer you're looking for? Browse other questions tagged or ask your own question.