Control Cost and Mahalanobis Distance Binary Hypothesis
Testing for Spacecraft Maneuver Detection
Author(s)
Jaunzemis, Adris D.
Advisor(s)
Holzinger, Marcus J.
Editor(s)
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Abstract
An anomaly hypothesis testing technique using the minimum-fuel control distance metric is extended
to incorporate non-Gaussian boundary condition uncertainties and employ binary hypothesis testing.
The adjusted control distance metric utilizes Gaussian mixtures to model non-Gaussian boundary
conditions, and binary hypothesis testing allows inclusion of anomaly detection thresholds and allow able error rates. An analogous framework accommodating Gaussian mixtures and binary hypothesis
testing is developed. Both algorithms are compared using simulated and empirical satellite maneu ver data. The North-South station-keeping scenario shows control distance to be less sensitive with
increased uncertainty than Mahalanobis distance but more consistent with respect to observation
gap duration, a trend which is corroborated using available real-world data. The same consistency
with respect to observation gap is observed in East-West station-keeping while also showing control
distance metric to be more sensitive for shorter observation gaps. In the non-Gaussian boundary con dition case, control distance outperforms Mahalanobis distance in both detection and computational
complexity.
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Date
2015-11-12
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Resource Type
Text
Resource Subtype
Masters Project
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