This thesis uses linear covariance analysis to model a landmark tracking camera for lunar navigation on manned missions during a loss of communication scenario. The research provides evidence that this method satisfies Crew Exploration Vehicle requirements for autonomous navigation for returning astronauts safely to Earth from lunar orbit. This study broadens NASA's existing research efforts by creating a 6-degree-of-freedom linear covariance analysis tool to simulate the navigation errors generated in lunar orbit in the absence of ground updates. This methodology is capable of generating results which approximate those of a Monte Carlo study in a fraction of the time. Evidence is shown that landmark tracking can substantially reduce position and velocity errors while actively tracking a realistic set of lunar features.
| Identifer | oai:union.ndltd.org:RICE/oai:scholarship.rice.edu:1911/20567 |
| Date | January 2007 |
| Creators | Osenar, Michael J. |
| Contributors | Spanos, Pol D., Clark, Fred D. |
| Source Sets | Rice University |
| Language | English |
| Detected Language | English |
| Type | Thesis, Text |
| Format | 102 p., application/pdf |
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