Date of Award
Master of Science
Department of Electrical and Computer Engineering
Stephen C. Cain, PhD.
This research paper investigates ways to improve the detection capability and predict the performance of the Space Surveillance Telescope (SST) system when it's relocated to Exmouth, Australia. The dataset collected by the SST observing the Geosynchronous Earth Orbit (GEO) satellite, ANIK-F1, entering the earth's eclipse is used to test the performance of the three existing and one new detection algorithm. The three existing algorithms are the point detection (Binary Hypothesis Test (BHT)), correlation detection (CD-BHT), and Multi-hypothesis Test using ten hypotheses (MHT10), and the new detection algorithm is the Multi-hypothesis Test using six hypotheses (MHT6). To improve the accuracy and validness of the comparison, a new method of obtaining the true atmospheric seeing parameter, terminator (point before the object entering the eclipse), and parameters used for the comparison are also investigated. It is found that the MHTs vastly outperform the BHTs, and the MHT6 offers a similar or improved performance over the MHT10, but requiring only half of the computing power.
DTIC Accession Number
Jeon, Jae H., "Improving the Performance of the Space Surveillance Telescope as a Function of Seeing Parameter" (2015). Theses and Dissertations. 36.