The signal/noise ratio is an important parameter of the spectrometer. Better the signal to noise ratio, better the spectrum’s quality. I am working in the Raman spectroscopy field. Based on the theoretical idea, the signal to noise ratio is directly proportional to √N. Here, N is the intensity (height) of the peak.
However, I like to measure the signal to noise ratio of the spectrometer.
Is there any way to measure the signal to noise ratio of the Raman spectrometer?
Mr. Vincent,
''S/N: The difference of peak and background signal, divided by the square root of the background signal.
The peak signal is measured at the H2O Raman peak (397 nm for 350 nm excitation) and the noise in a region (450 nm) where no Raman signal is present, and an "ideal" system would give a signal value of zero''
'' Excitation 350 nm with 5 nm bandpass Emission 365–450 nm with 5 nm bandpass Interval 0.5 nm Integration 1 s No smoothing of data points Standard room temperature, red sensitive, detector''
Companies that produce equipment often have their own protocol for signal-to-noise ration evaluation (see an example http://www.horiba.com/scientific/products/fluorescence-spectroscopy/signal-to-noise-ratio/). The use of these protocols is one of the best way for various substances. Of cause, there are some exceptions, and it also depends on your field.
Bojidarka B. Ivanova
added an answer, but H2O Raman peak used for photoluminescense S/N ratio, not for raman.
Thank you all ( Bojidarka B. Ivanova, Uttam Pal, Mykola Isaiev and E. Vasil'ev ) for useful discussion about this question.
If I am still on time I would suggest to use the standard deviation of the signal where no peaks are present, and the difference peak-bckd as the signal, since the noise in fact is the fluctuation of the background and not its mean value. It is true that in ideal conditions the main noise source is shot noise and then the sqrt indicates the standard deviation, but in real data other effects contribute to the noise (dark current, readout noise, ...) so the best thing is a direct estimation of the fluctuations.
However, this estimation is not perfectly true, since one should refer to the fluctuation having the same spatial frequency of the peaks under examination, but this would require a FFT analysis which is not really straightforward...
My answer comes with a delay but still...
I see a couple of comments saying that the SNR is the peak height over standard deviation of the background. This is not SNR. This value defines the visibility of a peak. Usually, three times (background noise) defines the smallest visible peak. Therefore, (peak height)/( background standard deviation) is not SNR. SNR is the mean of the peak intensity for a few spectra recorded consecutively, divided by the standard deviation of the same peak's intenstiy. Which means that you have a good SNR if peak height remains the same for all your measurements which were taken consecutively as opposed to measurements where signal intensity changes over time.
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