Invariant Theory as a Tool for Spacecraft Navigation

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AAS-22-746.pdf (293.7 KB)
Author(s)
Derksen, Harm
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Organizational Unit
Daniel Guggenheim School of Aerospace Engineering
The Daniel Guggenheim School of Aeronautics was established in 1931, with a name change in 1962 to the School of Aerospace Engineering
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https://hdl.handle.net/1853/74892
Abstract
Many spacecraft navigation algorithms are built upon models describing the geometric relationships between the spacecraft state and the measurement produced by a sensor. This is especially true for vision-based sensors. However, extracting the maximum amount of independent state information from a measurement (or set of measurements) is not always straightforward. This work investigates the utility of invariant theory as a tool to better utilize the information content within sensor data for spacecraft navigation. Direct applications include star pattern recognition, terrain relative navigation (TRN), and LIDAR point cloud registration.
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Date
2022-08
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Text
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Paper
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