Real-time noise reduction for Mössbauer spectroscopy through online implementation of a modified Kalman filter

David G. Abrecht; Jon M. Schwantes; Ravi K. Kukkadapu; Benjamin S. McDonald; Gregory C. Eiden; Lucas E. Sweet

doi:10.1016/j.nima.2014.10.053

Real-time noise reduction for Mössbauer spectroscopy through online implementation of a modified Kalman filter

David G. Abrecht, Jon M. Schwantes, Ravi K. Kukkadapu, Benjamin S. McDonald, Gregory C. Eiden, Lucas E. Sweet

Research output: Contribution to journal › Article › peer-review

9 Scopus citations

Abstract

Spectrum-processing software that incorporates a Gaussian smoothing kernel within the statistics of first-order Kalman filtration has been developed to provide cross-channel spectral noise reduction for increased real-time signal-to-noise ratios for Mössbauer spectroscopy. The filter was optimized for the breadth of the Gaussian using the Mössbauer spectrum of natural iron foil, and comparisons among the peak broadening, signal-to-noise ratios, and shifts in the calculated hyperfine parameters are presented. The results of optimization give a maximum improvement in the signal-to-noise ratio of 51.1% over the unfiltered spectrum at a Gaussian breadth of 27 channels, or 2.5% of the total spectrum width. The full-width half-maximum of the spectrum peaks showed an increase of 19.6% at this optimum point, indicating a relatively weak increase in the peak broadening relative to the signal enhancement, leading to an overall increase in the observable signal. Calculations of the hyperfine parameters showed that no statistically significant deviations were introduced from the application of the filter, confirming the utility of this filter for spectroscopy applications.

Original language	English
Pages (from-to)	66-71
Number of pages	6
Journal	Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
Volume	773
DOIs	https://doi.org/10.1016/j.nima.2014.10.053
State	Published - Feb 11 2015
Externally published	Yes

Funding

The authors would like to thank Drs. Sean Robinson and Rick Wittman for insightful comments and in-depth review. We would also like to acknowledge the Environmental Molecular Sciences Laboratory (EMSL), located at Pacific Northwest National Laboratory, for assistance with the Mössbauer efforts. This work was funded by Pacific Northwest National Laboratory utilizing Laboratory Directed Research and Development (LDRD) funds. Pacific Northwest National Laboratory is operated by Battelle Memorial Institute for the US Department of Energy under contract DE-AC06-76RLO-1830.

Funders	Funder number
Laboratory Directed Research and Development Program at Pacific Northwest National Laboratory
U.S. Department of Energy	DE-AC06-76RLO-1830
Battelle
Laboratory Directed Research and Development

Keywords

Mössbauer spectroscopy
Signal-to-noise ratio
Software
Spectrum filtering

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10.1016/j.nima.2014.10.053

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Abrecht, D. G., Schwantes, J. M., Kukkadapu, R. K., McDonald, B. S., Eiden, G. C., & Sweet, L. E. (2015). Real-time noise reduction for Mössbauer spectroscopy through online implementation of a modified Kalman filter. Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 773, 66-71. https://doi.org/10.1016/j.nima.2014.10.053

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abstract = "Spectrum-processing software that incorporates a Gaussian smoothing kernel within the statistics of first-order Kalman filtration has been developed to provide cross-channel spectral noise reduction for increased real-time signal-to-noise ratios for M{\"o}ssbauer spectroscopy. The filter was optimized for the breadth of the Gaussian using the M{\"o}ssbauer spectrum of natural iron foil, and comparisons among the peak broadening, signal-to-noise ratios, and shifts in the calculated hyperfine parameters are presented. The results of optimization give a maximum improvement in the signal-to-noise ratio of 51.1% over the unfiltered spectrum at a Gaussian breadth of 27 channels, or 2.5% of the total spectrum width. The full-width half-maximum of the spectrum peaks showed an increase of 19.6% at this optimum point, indicating a relatively weak increase in the peak broadening relative to the signal enhancement, leading to an overall increase in the observable signal. Calculations of the hyperfine parameters showed that no statistically significant deviations were introduced from the application of the filter, confirming the utility of this filter for spectroscopy applications.",

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Abrecht, DG, Schwantes, JM, Kukkadapu, RK, McDonald, BS, Eiden, GC & Sweet, LE 2015, 'Real-time noise reduction for Mössbauer spectroscopy through online implementation of a modified Kalman filter', Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, vol. 773, pp. 66-71. https://doi.org/10.1016/j.nima.2014.10.053

Real-time noise reduction for Mössbauer spectroscopy through online implementation of a modified Kalman filter. / Abrecht, David G.; Schwantes, Jon M.; Kukkadapu, Ravi K. et al.
In: Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 773, 11.02.2015, p. 66-71.

Research output: Contribution to journal › Article › peer-review

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T1 - Real-time noise reduction for Mössbauer spectroscopy through online implementation of a modified Kalman filter

AU - Abrecht, David G.

AU - Schwantes, Jon M.

AU - Kukkadapu, Ravi K.

AU - McDonald, Benjamin S.

AU - Eiden, Gregory C.

AU - Sweet, Lucas E.

PY - 2015/2/11

Y1 - 2015/2/11

N2 - Spectrum-processing software that incorporates a Gaussian smoothing kernel within the statistics of first-order Kalman filtration has been developed to provide cross-channel spectral noise reduction for increased real-time signal-to-noise ratios for Mössbauer spectroscopy. The filter was optimized for the breadth of the Gaussian using the Mössbauer spectrum of natural iron foil, and comparisons among the peak broadening, signal-to-noise ratios, and shifts in the calculated hyperfine parameters are presented. The results of optimization give a maximum improvement in the signal-to-noise ratio of 51.1% over the unfiltered spectrum at a Gaussian breadth of 27 channels, or 2.5% of the total spectrum width. The full-width half-maximum of the spectrum peaks showed an increase of 19.6% at this optimum point, indicating a relatively weak increase in the peak broadening relative to the signal enhancement, leading to an overall increase in the observable signal. Calculations of the hyperfine parameters showed that no statistically significant deviations were introduced from the application of the filter, confirming the utility of this filter for spectroscopy applications.

AB - Spectrum-processing software that incorporates a Gaussian smoothing kernel within the statistics of first-order Kalman filtration has been developed to provide cross-channel spectral noise reduction for increased real-time signal-to-noise ratios for Mössbauer spectroscopy. The filter was optimized for the breadth of the Gaussian using the Mössbauer spectrum of natural iron foil, and comparisons among the peak broadening, signal-to-noise ratios, and shifts in the calculated hyperfine parameters are presented. The results of optimization give a maximum improvement in the signal-to-noise ratio of 51.1% over the unfiltered spectrum at a Gaussian breadth of 27 channels, or 2.5% of the total spectrum width. The full-width half-maximum of the spectrum peaks showed an increase of 19.6% at this optimum point, indicating a relatively weak increase in the peak broadening relative to the signal enhancement, leading to an overall increase in the observable signal. Calculations of the hyperfine parameters showed that no statistically significant deviations were introduced from the application of the filter, confirming the utility of this filter for spectroscopy applications.

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ER -

Real-time noise reduction for Mössbauer spectroscopy through online implementation of a modified Kalman filter

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