Control Cost and Mahalanobis Distance Binary Hypothesis Testing for Spacecraft Maneuver Detection

Author(s)
Jaunzemis, Adris D.
Advisor(s)
Holzinger, Marcus J.
Editor(s)
Associated Organization(s)
Organizational Unit
Daniel Guggenheim School of Aerospace Engineering
The Daniel Guggenheim School of Aeronautics was established in 1931, with a name change in 1962 to the School of Aerospace Engineering
Supplementary to:
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.
Sponsor
Date
2015-11-12
Extent
Resource Type
Text
Resource Subtype
Masters Project
Rights Statement
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