Optimizing Data Reduction Procedures in Spatial Heterodyne Raman Spectroscopy with Applications to Planetary Surface Analogs

A spatial heterodyne Raman spectrometer (SHRS) is a variant of a Michelson interferometer in which the mirrors of a Michelson are replaced with two stationary diffraction gratings. When light enters the SHRS, it is reflected off of diffraction gratings at frequency-dependent angles that produce crossed wavefronts in space that can be imaged using a plane array detector. The crossed wavefronts, which represent a superposition of interference fringes, are converted to a Raman spectrum upon applying a Fourier transform. In this work, a new approach to intensity calibration is discussed that originates from modeling the shot noise produced by the SHRS and converting the real noise to idealized white noise as predicted by theory. This procedure has two effects. First, the technique produces Raman spectra with white noise. Second, when the mean of the noise is normalized to one, the technique produces Raman spectra where the intensity axis is equivalent to signal-to-noise ratio. The data reduction technique is then applied to the measurement of materials of interest to the planetary science community, including minerals and inorganic salts, at a distance of 5 m from the collecting optic.