[1] The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) is a hyperspectral imager on the Mars Reconnaissance Orbiter (MRO) spacecraft. CRISM consists of three subassemblies, a gimbaled Optical Sensor Unit (OSU), a Data Processing Unit (DPU), and the Gimbal Motor Electronics (GME). CRISM's objectives are (1) to map the entire surface using a subset of bands to characterize crustal mineralogy, (2) to map the mineralogy of key areas at high spectral and spatial resolution, and (3) to measure spatial and seasonal variations in the atmosphere. These objectives are addressed using three major types of observations. In multispectral mapping mode, with the OSU pointed at planet nadir, data are collected at a subset of 72 wavelengths covering key mineralogic absorptions and binned to pixel footprints of 100 or 200 m/pixel. Nearly the entire planet can be mapped in this fashion. In targeted mode the OSU is scanned to remove most along-track motion, and a region of interest is mapped at full spatial and spectral resolution (15-19 m/pixel, 362-3920 nm at 6.55 nm/channel). Ten additional abbreviated, spatially binned images are taken before and after the main image, providing an emission phase function (EPF) of the site for atmospheric study and correction of surface spectra for atmospheric effects. In atmospheric mode, only the EPF is acquired. Global grids of the resulting lower data volume observations are taken repeatedly throughout the Martian year to measure seasonal variations in atmospheric properties. Raw, calibrated, and map-projected data are delivered to the community with a spectral library to aid in interpretation.

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The NASA Autonomous Precision Landing and Hazard Avoidance Technology (ALHAT) program is developing an autonomous precision landing system capable of landing a spacecraft on the moon. To achieve the desired 90 m (3o) landing accuracy some version of a Terrain Relative Navigation (TRN) is necessary. One such algorithm is described in a companion paper. These algorithms require an accurate representation of the lunar terrain for both the on-board TRN algorithms and the ground-based software test bed (truth model) to verify the performance of the algorithms. In its terminal landing phase, the spacecraft will touchdown in a safe location using two algorithms: Hazard Detection and Avoidance (HDA) and the Hazard-Reference Navigation (HRN). To verify the performance of the HDA and HRN algorithms, ALHAT needs lunar surface models incorporating rock shape and size distribution statistics.

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