Since the launch of the first rocket by the scientists during the World War II , mankind continues their exploration of space. Those space explorations bring the benefits to human, such as high technology products like GPS, cell phone, etc. and in-depth insight of outside of the earth. However, they produce millions of debris with a total estimated mass of more than 3,000,000 kg in the space around the earth, which has and will continue to threat the safety of manned or unmanned space exploration. According to the research, at least tens of spacecraft were considered been damaged or destroyed by the debris left in the space. Thus, the increasingly cluttered environment in space is placing a premium on techniques capable of tracking and estimating the trajectory of space debris. Among debris, the pieces smaller than 1cm are unable to damage spacecraft because of the crafts’ shields, while the pieces larger than 10cm can be tracked by ground-based radars or a radar network. However, unlike the debris within these size ranges, the debris larger than 1 cm and smaller than 10 cm are able to hurt the shield of space craft and are hard to be detected by the exiting technical equipments because of their small size and cross-section area. Accordingly it is always a challenge for spacecraft or satellite mission designers to consider explicitly the ones ranged from 1 cm to 10 cm a priori. To tackle this challenge, a vision based debris’ trajectory tracking method is presented in the thesis. Unlike radar tracking, vision based tracking doesn’t require knowledge of a debris’ cross-section, regardless of its size. In this work, two cameras onboard of satellites in a formation are used to track the debris in iv close proximity. Also to differentiate the target debris from other clutters (i.e. the debris that are not tracked intentionally), a data association technique is investigated. A two-stage nonlinear robust controller is developed to adjust the attitude of the satellites such that the target debris is always inside of the field of view of the cameras. Capabilities of the proposed integrated estimation and control methods are validated in the simulations.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-3071 |
| Date | 01 January 2011 |
| Creators | Li, Ni |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations |
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