The purpose of this thesis is to create a search strategy to find orbital debris when the object fails to appear in the sky at its predicted location. This project is for NASA Johnson Space Center Orbital Debris Program Office through the MODEST (Michigan Orbital Debris Survey Telescope) program. This thesis will build upon the research already done by James Biehl in “Formulation of a Search Strategy for Space Debris at GEO.” MODEST tracks objects at a specific right ascension and declination. A circular orbit assumption is then used to predict the location of the object at a later time. Another telescope performs a follow-up to the original observation to provide a more accurate orbit predication. This thesis develops a search strategy when the follow-up is not successful. A general search strategy for finding space debris was developed based on previous observations. A GUI was also generated to find a search strategy in real-time for a specific object based upon previous observations of that object.
Search strategies were found by adding a 2% mean random error to the position and velocity vectors. Adding a random error allows for finding the most likely location of space debris when the orbital elements are slightly incorrect. A bivariate kernel density estimator was used to find the probability density function. The probability density function was used to find the most probable location of an object. A correlation between error in the orbital elements and error in right ascension and declination root mean square (RMS) error was investigated. It was found that the orbital elements affect the RMS error nonlinearly, but the relation between orbital element and error depended on the object and no general pattern was found. It was found that how long after the original object was found until the follow-up was attempted did not have a large impact on the probability density function or the search strategy.
| Identifer | oai:union.ndltd.org:CALPOLY/oai:digitalcommons.calpoly.edu:theses-1695 |
| Date | 01 November 2011 |
| Creators | Jackson, Daniel J |
| Publisher | DigitalCommons@CalPoly |
| Source Sets | California Polytechnic State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Master's Theses |
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