Abstract The Lunar Trailblazer mission aimed to assess the presence of water on the lunar surface using imaging spectroscopy in visible shortwave infrared (VSWIR) coupled with high‐resolution multispectral imaging in thermal midwave‐infrared (MWIR), captured simultaneously over the same target from orbit around the Moon with two different instruments. Uncertainties in clock timing, instrument models, and instrument pointing knowledge manifest as geospatial offsets between the two data sets that must be corrected in post‐processing to enable co‐registration, tying the acquired images to their precise latitudes and longitudes on the Moon. This work describes an algorithmic approach to co‐registering and geolocalizing images after acquisition without high precision instrument and spacecraft pointing models, the Iterative Matching Pipeline for Post‐Acquisition Image Localization (IMPPAIL), utilizing previously acquired data for development. We use Lunar Orbiter Laser Altimetry (LOLA) and Kaguya data to make shaded relief maps as the basemap on which to project data. To test our processing pipeline prior to Lunar Trailblazer data collection, we use Moon Mineralogy Mapper (M 3 ) data for VSWIR images and simulated MWIR images. When demonstrated on these data sets, IMPPAIL produces a 98% success rate registering VSWIR data to LOLA/Kaguya shaded relief maps and successfully co‐registered MWIR and VSWIR in all four simulation cases. We include a code package with software tools allowing this algorithm to be used for a variety of data sets across many other missions.
Gauld et al. (Fri,) studied this question.