Sparse Channel Estimation and Tracking for Underwater Acoustic Communications
dc.contributor.author | Yin, Danqing | |
dc.contributor.copyright-release | Not Applicable | en_US |
dc.contributor.degree | Master of Applied Science | en_US |
dc.contributor.department | Department of Electrical & Computer Engineering | en_US |
dc.contributor.ethics-approval | Not Applicable | en_US |
dc.contributor.external-examiner | n/a | en_US |
dc.contributor.graduate-coordinator | Dr. Jason Gu | en_US |
dc.contributor.manuscripts | Not Applicable | en_US |
dc.contributor.thesis-reader | Dr. Christian Schlegel | en_US |
dc.contributor.thesis-reader | Dr. Peter Vanberkel | en_US |
dc.contributor.thesis-supervisor | Dr. Dmitry Trukhachev | en_US |
dc.date.accessioned | 2016-12-15T12:30:45Z | |
dc.date.available | 2016-12-15T12:30:45Z | |
dc.date.defence | 2016-12-06 | |
dc.date.issued | 2016-12-15T12:30:45Z | |
dc.description.abstract | This thesis focuses on estimation and tracking of underwater acoustic channels. A model of underwater acoustic channel suitable to study the channel estimation problem is constructed. The model is used together with a Bellhop acoustic wave propagation simulator to generate channels for various propagation environments, depths and distances, and we studied their sparseness and variation properties. Finally a number of estimation methods such as basis pursuit and approximate message passing are adapted to channel estimation problems and tested on a number of channels. Window-based and Kalman- filter based channel tracking is also studied. A detailed comparison of estimation and tracking methods is presented. | en_US |
dc.identifier.uri | http://hdl.handle.net/10222/72583 | |
dc.language.iso | en | en_US |
dc.title | Sparse Channel Estimation and Tracking for Underwater Acoustic Communications | en_US |
dc.type | Thesis | en_US |
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