Computes the Allan variance of a data set.
Remarks
This implementation computes the fully overlapped Allan variance using the method presented by Yadav et. al.
Yadav, Shrikanth & Shastri, Saurav & Chakravarthi, Ghanashyam & Kumar, Viraj & Rao, Divya & Agrawal, Vinod. (2018). A Fast, Parallel Algorithm for Fully Overlapped Allan Variance and Total Variance for Analysis and Modeling of Noise in Inertial Sensors. IEEE Sensors Letters. PP. 1-1. 10.1109/LSENS.2018.2829799.
| Type | Intent | Optional | Attributes | Name | ||
|---|---|---|---|---|---|---|
| real(kind=real64), | intent(in), | dimension(:) | :: | x |
The N-element data set to analyze. |
|
| real(kind=real64), | intent(in), | optional | :: | dt |
An optional input specifying the time increment between samples in x. If not specified, this value is set to 1. |
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| class(errors), | intent(inout), | optional, | target | :: | err |
A mechanism for communicating errors and warnings to the caller. Possible warning and error codes are as follows. - FS_NO_ERROR: No errors encountered. - FS_MEMORY_ERROR: Occurs if there is a memory allocation error. |
An M-by-2 array containing the results where M is N / 2 - 1 if N is even; else, M is (N - 1) / 2 - 1 if N is odd. The first column contains the averaging times associated with the M results stored in the second column.