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dc.contributor.advisorHolzinger, Marcus J.
dc.contributor.authorMurphy, Timothy S.
dc.date.accessioned2018-05-31T18:16:38Z
dc.date.available2018-05-31T18:16:38Z
dc.date.created2018-05
dc.date.issued2018-04-06
dc.date.submittedMay 2018
dc.identifier.urihttp://hdl.handle.net/1853/59930
dc.description.abstractThis dissertation explores the following. Coordinating a large network of electo-optical sensors (EOS) for an effective Space Surveillance Network requires several novel capabilities. The first piece of this work involves the search set, or the set of orbits which may contain relevant object(s). A tasking algorithm is needed to optimally choose a trajectory through the sky that a sensor should take to search a set of orbits. Because of the malleable definition of a set, this allows EOS to be tasked on a wide variety of search and reacquisition problems. Next, when taking actual data the sensor exposure time, slew rate, and campaign length need to be chosen to optimize the quality of image data. These tasking parameters are chosen with respect to the detection and estimation algorithms themselves, which all relate back to a maximum likelihood method. Next, the object detection algorithms should be as sensitive as possible. This enables a larger network of lower cost telescopes to be deployed, and ensures that performance is robust to light pollution, enabling new telescope locations. These types of networks are needed to allow the kinds of sensor architectures which support interesting handoff and reacquisition problems. Finally, to make proper telescope communication, hand-off, and long term reacquisition possible, detection algorithms should utilize any prior information (search set) on a particular object or class of objects for more sensitive and efficient detection. This supports hand-off between arbitrary locations and longer delay times before reacquisition from the detection side of the problem.
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherGeorgia Institute of Technology
dc.subjectSpace situational awareness
dc.subjectOptical sensors
dc.subjectTasking
dc.subjectOrbit estimation
dc.subjectComputer vision
dc.titleIntegrated tasking, processing, and orbit determination for optical sensors in a space situational awareness framework
dc.typeDissertation
dc.description.degreePh.D.
dc.contributor.departmentAerospace Engineering
thesis.degree.levelDoctoral
dc.contributor.committeeMemberJohnson, Eric
dc.contributor.committeeMemberLightsey, Glen
dc.contributor.committeeMemberFlewelling, Brien
dc.contributor.committeeMemberSabol, Chris
dc.date.updated2018-05-31T18:16:38Z


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