1 Ocak 2010 Konferans bildirisi Açık Erişim

Yoldemir, Ahmet Burak; Sezgin, Mehmet

DataCite XML

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  <identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/92835</identifier>
  <creators>
    <creator>
      <creatorName>Yoldemir, Ahmet Burak</creatorName>
      <givenName>Ahmet Burak</givenName>
      <familyName>Yoldemir</familyName>
      <affiliation>TUBITAK UEKAE, Gebze, Kocaeli, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Sezgin, Mehmet</creatorName>
      <givenName>Mehmet</givenName>
      <familyName>Sezgin</familyName>
      <affiliation>TUBITAK UEKAE, Gebze, Kocaeli, Turkey</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Real-Time Buried Object Detection Using Lmmse Estimation</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2010</publicationYear>
  <dates>
    <date dateType="Issued">2010-01-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Conference paper</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/92835</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.81043/aperta.92834</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.81043/aperta.92835</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
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  <descriptions>
    <description descriptionType="Abstract">We present the application of linear minimum mean square error (LMMSE) estimation to GPR data for achieving buried object detection. Without employing any empirical assumptions, nonstationary form of Wiener-Hopf equations is applied to GPR signals to estimate the next sample in normal conditions. A large deviation from this estimation indicates the presence of a buried object. The technique is causal, which allows it to be used in real-time applications. Our approach is theoretically optimal in linear minimum mean square error sense, and it is also validated with the tests that are carried out on a comprehensive data set of GPR signals.</description>
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