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In this paper a new image processing technique for flash LIDAR data is presented as a potential tool to enable
safe and precise spacecraft landings in future robotic or crewed lunar and planetary missions. Flash LIDARs
can generate, in real-time, range data that can be interpreted as a 3-dimensional (3-D) image and transformed
into a corresponding digital elevation map (DEM). The NASA Autonomous Landing and Hazard Avoidance
(ALHAT) project is capitalizing on this new technology by developing, testing and analyzing flash LIDARs
to detect hazardous terrain features such as craters, rocks, and slopes during the descent phase of spacecraft
landings. Using a flash LIDAR for this application looks very promising, however through theoretical and
simulation analysis the ALHAT team has determined that a single frame, or mosaic, of flash LIDAR data may
not be sufficient to build a landing site DEM with acceptable spatial resolution, precision, size, or for a mosaic,
in time, to meet current system requirements. One way to overcome this potential limitation is by enhancing
the flash LIDAR output images. We propose a new super-resolution algorithm applicable to flash LIDAR range
data that will create a DEM with sufficient accuracy, precision and size to meet current ALHAT requirements.
The performance of our super-resolution algorithm is analyzed by processing data generated during a series of
simulation runs by a high fidelity model of a flash LIDAR imaging a high resolution synthetic lunar elevation
map. The flash LIDAR model is attached to a simulated spacecraft by a gimbal that points the LIDAR to a
target landing site. For each simulation run, a sequence of flash LIDAR frames is recorded and processed as
the spacecraft descends toward the landing site. Each run has a different trajectory profile with varying LIDAR
look angles of the terrain. We process the output LIDAR frames using our SR algorithm and the results show
that the achieved level of accuracy and precision of the SR generated landing site DEM is more than adequate
for detecting hazardous terrain features and identifying safe areas.
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