Vibration-coherent noise removal

From Atomix

The shear probe, like nearly all other velocity sensors, measures the velocity of the fluid relative to the platform that holds the probe. Thus, platform vibrations induce a signal that is due to platform motions and does not represent environmental shear.

The algorithm described by Goodman et al (2006)[1] is often used to remove vibration-induced components from shear-probe spectra. This algorithm estimates the transfer functions that relate the vibration (or acceleration) signals to the shear-probe signals. Like all transfer function estimates, the algorithm relies on the coherency between the shear-probe and vibration signals in order to achieve a statistically significant estimate of the transfer functions among these signals.

Focusing on one specific direction, one specific shear probe, one can simply:

- compute the coherence squared [math]\displaystyle{ \Gamma^2(f) }[/math] between the observed velocity or shear frequency spectrum [math]\displaystyle{ E_{\mathrm{obs}}(f) }[/math] and the vibration frequency spectrum [math]\displaystyle{ E_{\mathrm{vib}}(f) }[/math].

- and remove the vibration-coherent content of the shear spectrum using [math]\displaystyle{ E_{\mathrm{clean}}(f)=E_{\mathrm{obs}}(f)(1-\Gamma^2(f)) }[/math]

The statistical significance increases with increasing number of fft-segments used to make a spectral estimate. However, this removal biases the spectrum of shear low, in a wavenumber-independent manner, and must be corrected [2].

A desire to achieve a high spatial resolution of [math]\displaystyle{ \varepsilon }[/math]-estimates by using short lengths of data with few fft-segments conflicts with the need to achieve good statistical reliability of the transfer function and, thus, the correction for vibration induced signals.

References

  1. Goodman, L., Levine, E. R., & Lueck, R. G. (2006). On measuring the terms of the turbulent kinetic energy budget from an AUV. Journal of Atmospheric and Oceanic Technology, 23(7), 977-990.
  2. Lueck, R. G., 2022: The bias in coherent-noise removal. Journal of Atmospheric and Oceanic Technology –, submitted, doi:--.



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