The Goodman algorithm: Difference between revisions
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Focusing on one specific direction, one specific shear probe, one can simply: | Focusing on one specific direction, one specific shear probe, one can simply: | ||
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- and remove the vibration-coherent content of the shear spectrum using <math>E_{\mathrm{clean}}(f)=E_{\mathrm{obs}}(f)(1-\Gamma^2(f))</math> | - and remove the vibration-coherent content of the shear spectrum using <math>E_{\mathrm{clean}}(f)=E_{\mathrm{obs}}(f)(1-\Gamma^2(f))</math> | ||
where <math>E_{\mathrm{clean}}(f)</math> is the corrected shear frequency spectrum. Equation 3 in | where <math>E_{\mathrm{clean}}(f)</math> is the corrected shear frequency spectrum. Equation 3 in [https://journals.ametsoc.org/view/journals/atot/23/7/jtech1889_1.xml Goodman et al. 2006] Goodman et al. 2006 presents the formalism for a correction using multiple directions (multivariate approach). The multivariate approach is more efficient and, almost a requirement for powered vehicles like AUVs. The number of vibration (or acceleration) signals used to correct the observed spectra of shear should be included in the quality control flag. | ||
To obtain statistical significance, it is recommended to compute the coherence/cross-spectra over 7 fft-segments. The vibration-coherent noise removal algorithm [[The_bias_induced_by_the_Goodman_algorithm| biases low]] the spectrum of shear in a frequency independent manner, and can be corrected using the number of vibration (or other types) of signals used to correct the measured shear spectra and the number of fit-segments used to estimate the shear spectrum. | To obtain statistical significance, it is recommended to compute the coherence/cross-spectra over 7 fft-segments. The vibration-coherent noise removal algorithm [[The_bias_induced_by_the_Goodman_algorithm| biases low]] the spectrum of shear in a frequency independent manner, and can be corrected using the number of vibration (or other types) of signals used to correct the measured shear spectra and the number of fit-segments used to estimate the shear spectrum. | ||
Revision as of 15:45, 7 June 2024
The procedure is well described in Goodman et al. 2006 [1]. 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]
where [math]\displaystyle{ E_{\mathrm{clean}}(f) }[/math] is the corrected shear frequency spectrum. Equation 3 in Goodman et al. 2006 Goodman et al. 2006 presents the formalism for a correction using multiple directions (multivariate approach). The multivariate approach is more efficient and, almost a requirement for powered vehicles like AUVs. The number of vibration (or acceleration) signals used to correct the observed spectra of shear should be included in the quality control flag.
To obtain statistical significance, it is recommended to compute the coherence/cross-spectra over 7 fft-segments. The vibration-coherent noise removal algorithm biases low the spectrum of shear in a frequency independent manner, and can be corrected using the number of vibration (or other types) of signals used to correct the measured shear spectra and the number of fit-segments used to estimate the shear spectrum. [2].
References
- ↑ L. Goodman and E. Levine and R. Lueck. 2006. On measuring the terms of the turbulent kinetic energy budget from an AUV. J. Atmos. Oceanic Technol.. doi:10.1175/JTECH1889.1
- ↑ R. G. Lueck, D. MacIntyre and and J. MacMillan. 2022. The bias in coherent noise removal. J. Atmos. Oceanic Technol.. doi:TBD
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