Multichannel blind deconvolution in underwater acoustic channels

dc.contributor.advisor Romberg, Justin
dc.contributor.author Tian, Ning
dc.contributor.committeeMember Sabra, Karim
dc.contributor.committeeMember McClellan, James
dc.contributor.committeeMember Davenport, Mark
dc.contributor.committeeMember Rozell, Christopher
dc.contributor.department Electrical and Computer Engineering
dc.date.accessioned 2018-05-31T18:15:49Z
dc.date.available 2018-05-31T18:15:49Z
dc.date.created 2018-05
dc.date.issued 2018-04-10
dc.date.submitted May 2018
dc.date.updated 2018-05-31T18:15:49Z
dc.description.abstract This thesis developed new techniques for solving the multichannel blind deconvolution problem and implemented these techniques in acoustic waveguide multiple environment. We developed a systematic way to build an efficient and accurate channel models incorporating a priori information about the expected Channel Impulse Responses' (CIRs) arrival-time structure. Based on the linear and bilinear channel models in the underwater acoustic applications, we solved the problem using two approaches. In the first approach, we formulated the problem as solving a system of bilinear equations, which in turn can be recast as recovering a low-rank matrix from a set of linear observations. In the second approach, we formed a cross-correlation matrix from the channel outputs and solved the problem by minimizing a quadratic function over a non-convex set. We demonstrated the efficiency and robustness of both multichannel blind deconvolution methods on realistic acoustic channels in ocean waveguides and experimentally validated the methods using at-sea data. In the end, we investigated methods to learn the subspace of CIRs directly from multiple snapshots in the context of solving multichannel blind deconvolution.
dc.description.degree Ph.D.
dc.format.mimetype application/pdf
dc.identifier.uri http://hdl.handle.net/1853/59906
dc.language.iso en_US
dc.publisher Georgia Institute of Technology
dc.subject Multichannel blind deconvolution
dc.subject Low-rank recovery
dc.subject Cross-convolution methods
dc.subject Non-convex optimizations
dc.title Multichannel blind deconvolution in underwater acoustic channels
dc.type Text
dc.type.genre Dissertation
dspace.entity.type Publication
local.contributor.advisor Romberg, Justin
local.contributor.corporatename School of Electrical and Computer Engineering
local.contributor.corporatename College of Engineering
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relation.isOrgUnitOfPublication 5b7adef2-447c-4270-b9fc-846bd76f80f2
relation.isOrgUnitOfPublication 7c022d60-21d5-497c-b552-95e489a06569
thesis.degree.level Doctoral
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