In this context, we present the Computational Reconfigurable Imaging Spectrometer (CRISP), a new imaging spectrometer with current focus in the longwave infrared regime. The CRISP sensing approach exploits platform motion, dispersive elements, and coded sensing techniques to make a time series of encoded measurements of the optical spectrum at each pixel. This encoding is inverted using specialized processing to recover the spectrum. We will show that this sensing approach offers significant SNR and other advantages over existing conventional imaging spectrometer approaches, enabling lower SWaP and improved area coverage. In particular, CRISP enables high performance from smaller and less-expensive components such as uncooled microbolometers, and is thus more suitable than previous designs for small satellites that can be deployed in constellations. We also show that with a change of mask encoding and scanning mode, CRISP can be reconfigured to respond to new observations by a different spatial/spectral encoding design, allowing area coverage rate, spatial resolution and spectral resolution to be traded off.
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This material is based upon work supported by the National Aeronautics and Space Administration under Air Force Contract No. FA8702-15-D-0001. Any opinions, findings, conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Aeronautics and Space Administration .