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dc.contributor.authorCarlton, Ashley
dc.contributor.authorMorgan, Rachel
dc.contributor.authorLohmeyer, Whitney
dc.contributor.authorCahoy, Kerri
dc.date.accessioned2018-05-19T12:42:20Z
dc.date.available2018-05-19T12:42:20Z
dc.date.issued2018-05-19
dc.identifier.urihttp://hdl.handle.net/1721.1/115526
dc.description.abstractAlgorithms have been developed that identify unusual behavior in satellite health telemetry. Telemetry from solid-state power amplifiers and amplifier thermistors from 32 geostationary Earth orbit communications satellites from 1991 to 2015 are examined. Transient event detection and change-point event detection techniques that use a sliding window-based median are used, statistically evaluating the telemetry stream compared to the local norm. This approach allows application of the algorithms to any spacecraft platform because there is no reliance in the algorithms on satellite- or component-specific parameters, and it does not require a priori knowledge about the data distribution. Individual telemetry data streams are analyzed with the event detection algorithms, resulting in a compiled list of unusual events for each satellite. This approach identifies up to six events of up to six events that affect 51 of 53 telemetry streams at once, indicative of a spacecraft system-level event. In two satellites, the same top event date (4 December 2008) occurs over more than 10 years of telemetry from both satellites. Of the five spacecraft with known maneuvers, the algorithms identify the maneuvers in all cases. Event dates are compared to known operational activities, space weather events, and available anomaly lists to assess the use of event detection algorithms for spacecraft monitoring and sensing of the space environment.en_US
dc.description.sponsorshipThe authors would like to acknowledge the U.S. Air Force Office of Sponsored Research grant FA9550-13-1-0099 and NASA for funding this work through NASA Space Technology and Research Fellowship grant NNX16AM74H.en_US
dc.titleTelemetry Fault-Detection Algorithms: Applications for Spacecraft Monitoring and Space Environment Sensingen_US
dc.typeArticleen_US


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