DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Binhee | ko |
dc.contributor.author | Kong, Seung-Hyun | ko |
dc.date.accessioned | 2013-03-29T16:49:50Z | - |
dc.date.available | 2013-03-29T16:49:50Z | - |
dc.date.created | 2013-01-16 | - |
dc.date.created | 2013-01-16 | - |
dc.date.created | 2013-01-16 | - |
dc.date.issued | 2012-04 | - |
dc.identifier.citation | ION PLANS 2012, pp.1295 - 1299 | - |
dc.identifier.uri | http://hdl.handle.net/10203/172273 | - |
dc.description.abstract | This paper presents an SVD-periodogram method for synthetic aperture radar (SAR) imaging. The purpose of this work is to improve resolution and target separability of SAR images. An advantage of the SVD-periodogram method is noise robustness, reduction of sidelobes and resolution of spectral estimation. In this paper, it is demonstrated that the SVD-periodogram method shows better performance than the matched filtering method and the conventional super-resolution multiple signal classification (MUSIC) method in SAR image processing. The targets to be separated are modeled, and this modeled data is used to demonstrate the performance of algorithms. | - |
dc.language | English | - |
dc.publisher | The Institute of Navigation | - |
dc.title | SAR Image Processing Using Super Resolution Spectral Estimation with SVD-Periodogram Method | - |
dc.type | Conference | - |
dc.identifier.wosid | 000309273900160 | - |
dc.identifier.scopusid | 2-s2.0-84866245759 | - |
dc.type.rims | CONF | - |
dc.citation.beginningpage | 1295 | - |
dc.citation.endingpage | 1299 | - |
dc.citation.publicationname | ION PLANS 2012 | - |
dc.identifier.conferencecountry | US | - |
dc.identifier.conferencelocation | South Carolina | - |
dc.embargo.liftdate | 9999-12-31 | - |
dc.embargo.terms | 9999-12-31 | - |
dc.contributor.localauthor | Kong, Seung-Hyun | - |
dc.contributor.nonIdAuthor | Kim, Binhee | - |
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