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Title: Remote sensing of ocean, ice and land surfaces using bistatically scattered GNSS signals from low Earth orbit
Author: Gleason, Scott
ISNI:       0000 0001 3500 8510
Awarding Body: University of Surrey
Current Institution: University of Surrey
Date of Award: 2006
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The use of bistatically reflected global navigation satellite system (GNSS) signals as a means of sensing the Earth has been advancing rapidly in recent years. This technique is founded on the basic principle of detecting GNSS signals, such as those of the Global Positioning System constellation (GPS), after they have reflected from the Earth's surface and using them to determine remotely the properties of the reflecting surface. Most of the existing research has been based on near-Earth experiments involving aircraft, elevated platforms, overhanging cliffs or from high altitude balloons. A limited number of signals have been detected in space using a very high gain antenna. However, it was uncertain if this could be repeated using a more modest configuration. There have been near-Earth based experiments designed to utilize GNSS reflected signals to extract information on the ocean wind and waves (scatterometry), ocean mean height (altimetry), sea ice sensing and the extraction of land surface topography and near surface soil moisture. In order to extend these applications to a global scale, further validation of the remote sensing potential of this technique is necessary using data from a spacecraft. This research will concentrate on connecting Earth reflected GPS signals to the ocean winds and waves and in demonstrating the potential of land and sea ice reflected signals using a spaceborne instrument with a medium gain antenna. The experimental basis for this research is the passive GPS bistatic radar experiment included on the United Kingdom's Disaster Monitoring Constellation (UK-DMC) satellite launched in October 2003 into a 680km sun synchronous orbit. Using this experiment several data sets have been collected over ocean, ice and land surfaces with reflected signals recovered on all attempts. These data sets provide the foundation for this research.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available