Uncorrelated Track Classification, Characterization, & Prioritization using Admissible Regions and Bayesian Inference

Marcus Holzinger (Georgia Institute of Technology)

Keywords: SSA, characterization, sensor tasking, uncorrelated tracks, admissible regions, bayesian

Abstract:

This paper introduces and discusses a method to rigorously classify and prioritize UCTs using Bayesian inference and admissible regions. A detailed derivation and discussion of the methodology is given, followed by a generalized definition of prioritization parameters. Several example prioritization parameters including `time left to detect,’ ‘zero-effort miss,’ and `effective albedo-area’ are motivated and given. A number of illustrative applications with optical UCTs are examined to demonstrate information that can be extracted from each observation. Finally, the information extracted from each UCT is then compared and approaches to observation prioritization discussed.

Date of Conference: September 9-12, 2014

Track: Astrodynamics

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