Instrument Response

In a previous blog I have described a Python script with a GUI for calibrating and processing meteor spectra. The spectrum calibrated in wavelength is still not the final result of the processing. One would like to have a plot of energy against wavelength. Unfortunately the measured intensity is influenced by detector sensitivity, grating efficiency, transmission of optics (window, lens, filters) and atmospheric transmittance (all wavelength dependent).

As long as we are interested in only the relative intensities (in order to determine chemical composition ratios e.g.), the different contributions for the detector signal can be combined with

I(λ) = IR(λ) * Tatm(λ) * S(λ)

Quite often the instrument response and atmospheric transmission are combined into an overall response

R(λ)  = IR(λ) * Tatm(λ)

From this equation the instrument response corrected spectrum is calculated as

S(λ) = I(λ) /R(λ)

With this equation the spectral energy distribution of the meteor can be calculated. Further details on the response function and its implementation are described in an IMC 2016 conference paper or in more detail in a manual describing the processing of meteor spectra with different spectroscopic tools.

Implementation in the Python script

This blog describes a practical implementation of the determination of th response function from observed bright stars with known calibrated spectra. This response function can then be applied to processed and calibrated meteor spectra. In addition some tools have been added to process the spectra (background subtraction for star spectra, Gaussian filtering, conversion ofwavelength from A <–> nm, conversion of higher order spectra to wavelength etc.). In the GUI an additional tab “Instrument Response” has been added for these operations:

calculation of instrument response

The image shows the calculation of the instrument response. The start spectrum (in this case Venus) and the calibration reference spectrum are loaded, then divided and suitably smoothed with a spline algorithm.

In the next step an actual meteor spectrum is divided by the instrument response, resulting in a spectral energy distribution spectrum:

red: measured spectrum, blue: response corrected spectrum

The Python script for meteor spectra processing including instrument response correction is available from Github, together with the manual and example files:

https://github.com/meteorspectroscopy/meteor-spectrum-calibration/tree/response

Since it has not been tested, it is in a branch for testing. The older script without response, but more thoroughly tested, is still available at:

https://github.com/meteorspectroscopy/meteor-spectrum-calibration

If you start with Python, it is advisable to download the tested version (You can download the project including demo files and manual with the green button “-> Code”, then select “download zip”). Then continue with reading the manual for installation and processing meteor spectra.

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