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dc.contributor.advisorKerri L. Cahoy.en_US
dc.contributor.authorCarlton, Ashley Kellyen_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Aeronautics and Astronautics.en_US
dc.date.accessioned2016-12-05T19:54:43Z
dc.date.available2016-12-05T19:54:43Z
dc.date.copyright2016en_US
dc.date.issued2016en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/105607
dc.descriptionThesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2016.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 103-116).en_US
dc.description.abstractConstellations of hundreds of low-Earth orbiting small satellites are currently being designed and built. Operators plan to provide data and media distribution services as well as imaging and weather observations. As our society increases its dependence on satellite services for communication and navigation, there is a growing need for efficient spacecraft systems monitoring and space situational awareness to avoid service interruptions due to hazards such as space weather. Particularly for large constellations, satellites need greater autonomy to improve responsivity and reduce the load on human operators. In this thesis, we present the development of algorithms that identify unusual behavior in satellite health telemetry. Once these events have been identified, we collect and analyze them, along with assessing space weather observations and operational environment factors. Our approach uses transient event detection and change-point event detection techniques, statistically evaluating the telemetry stream compared to a local norm. This approach allows us to apply our algorithms to any spacecraft platform, since there is no reliance on satellite- or component-specific parameters, and it does not require a priori knowledge about the data distribution. We apply these techniques to individual telemetry data streams on geostationary Earth orbit (GEO) communications satellites (ComSats), and consider the results, a compiled list of unusual events for each satellite. Results include being able to identify events that affect many telemetry streams at once, indicative of a spacecraft system-level event. With data from multiple satellites, we can use these methods to better determine whether external factors played a role. We compare event dates to known operational activities and to known space weather events to assess the use of event detection algorithms for spacecraft monitoring and for environmental sensing.en_US
dc.description.statementofresponsibilityby Ashley Kelly Carlton.en_US
dc.format.extent116 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectAeronautics and Astronautics.en_US
dc.titleFault detection algorithms for spacecraft monitoring and environmental sensingen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Aeronautics and Astronautics.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Aeronautics and Astronautics
dc.identifier.oclc962485672en_US


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