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The Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) Sensor Module (SM) Engineering Demonstration
Unit (EDU) is a high resolution spectral imager designed to measure infrared (IR) radiances using a
Fourier transform spectrometer (FTS). The GIFTS instrument employs three focal plane arrays (FPAs), which
gather measurements across the long-wave IR (LWIR), short/mid-wave IR (SMWIR), and visible spectral bands.
The raw interferogram measurements are radiometrically and spectrally calibrated to produce radiance spectra,
which are further processed to obtain atmospheric profiles via retrieval algorithms. This paper describes the
GIFTS SM EDU Level 1B algorithms involved in the calibration. The GIFTS Level 1B calibration procedures
can be subdivided into four blocks. In the first block, the measured raw interferograms are first corrected for
the detector nonlinearity distortion, followed by the complex filtering and decimation procedure. In the second
block, a phase correction algorithm is applied to the filtered and decimated complex interferograms. The resulting
imaginary part of the spectrum contains only the noise component of the uncorrected spectrum. Additional
random noise reduction can be accomplished by applying a spectral smoothing routine to the phase-corrected
spectrum. The phase correction and spectral smoothing operations are performed on a set of interferogram
scans for both ambient and hot blackbody references. To continue with the calibration, we compute the spectral
responsivity based on the previous results, from which, the calibrated ambient blackbody (ABB), hot blackbody
(HBB), and scene spectra can be obtained. We now can estimate the noise equivalent spectral radiance (NESR)
from the calibrated ABB and HBB spectra. The correction schemes that compensate for the fore-optics offsets
and off-axis effects are also implemented. In the third block, we developed an efficient method of generating
pixel performance assessments. In addition, a random pixel selection scheme is designed based on the pixel
performance evaluation. Finally, in the fourth block, the single pixel algorithms are applied to the entire FPA.
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