Show simple item record

dc.contributor.advisorMichael J. Ricard and Juan Pablo Vielma.en_US
dc.contributor.authorBurnham, Katherine Lee.en_US
dc.contributor.otherMassachusetts Institute of Technology. Operations Research Center.en_US
dc.date.accessioned2020-09-15T21:50:48Z
dc.date.available2020-09-15T21:50:48Z
dc.date.copyright2020en_US
dc.date.issued2020en_US
dc.identifier.urihttps://hdl.handle.net/1721.1/127297
dc.descriptionThesis: S.M., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, May, 2020en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 89-92).en_US
dc.description.abstractThis thesis presents a method for information fusion for an unmanned underwater vehicle (UUV).We consider a system that fuses contact reports from automated information system (AIS) data and active and passive sonar sensors. A linear assignment problem with learned assignment costs is solved to fuse sonar and AIS data. Since the sensors operate effectively at different depths, there is a time lag between AIS and sonar data collection. A recurrent neural network predicts a contact's future occupancy grid from a segment of its AIS track. Assignment costs are formed by comparing a sonar position with the predicted occupancy grids of relevant vessels. The assignment problem is solved to determine which sonar reports to match with existing AIS contacts.en_US
dc.description.statementofresponsibilityby Katherine Lee Burnham.en_US
dc.format.extent92 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectOperations Research Center.en_US
dc.titleInformation fusion for an unmanned underwater vehicle through probabilistic prediction and optimal matchingen_US
dc.title.alternativeInformation fusion for an UUV through probabilistic prediction and optimal matchingen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Operations Research Centeren_US
dc.contributor.departmentSloan School of Management
dc.identifier.oclc1191901156en_US
dc.description.collectionS.M. Massachusetts Institute of Technology, Sloan School of Management, Operations Research Centeren_US
dspace.imported2020-09-15T21:50:47Zen_US
mit.thesis.degreeMasteren_US
mit.thesis.departmentSloanen_US
mit.thesis.departmentOperResen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record