Date of Award


Document Type


Degree Name

Master of Science


Department of Electrical and Computer Engineering

First Advisor

Stephen C. Cain, PhD.


Current methods of dim object detection for space surveillance make use of a Gaussian log-likelihood-ratio-test-based detector that only considers the probability that a single point in an image resulted from the propagation of a point source through space. This paper proposes the application of a correlating Gaussian log-likelihood-ratio-test-based detector, which makes use of all the pixels in the window, to the arena of dim object detection. The requirements for comparing these detectors using the same threshold of detection are established. The performance of the detectors is compared using images taken by the Space Surveillance Telescope in New Mexico of a geostationary satellite as it goes into and out of eclipse during the vernal equinox March 13-15, 2012. The correlator is determined to offer superior performance based on a comparison of the relative probability of both algorithms to detect objects near the threshold of detection, among other metrics. The additional computational cost of implementation of the correlating detector is analyzed and determined.

AFIT Designator


DTIC Accession Number