Analytical Methods in Crater Rim Fitting and Pattern Recognition

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AAS_23-362.pdf (10.15 MB)
Author(s)
Krause, Michael
Price, Jonathan
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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/1853/74864
Abstract
Upcoming lunar missions are expected to utilize optical measurements for navigation. View invariants enable "lost-in-space" terrain relative navigation about cratered celestial bodies. Lunar crater rims form ellipses when imaged. Noisy measurements of points lying along this rim will be obtained, and may be fit to an ellipse to calculate the invariants. Hyper least squares (HLS) provides an attractive performance benefit compared to traditional (or total) least squares for this task. An analytical derivation of the covariance of these invariants in the presence of noise is presented, and is used to analyze performance of the invariants in realistic situations.
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2023-08
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