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Comparison of Proposed Target Tracking Algorithm, GRNN alpha, to Kalman Filter in 3D Environment

Kaplan, Gulay Buyukaksoy; Lana, Adnan


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  <identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/91445</identifier>
  <creators>
    <creator>
      <creatorName>Kaplan, Gulay Buyukaksoy</creatorName>
      <givenName>Gulay Buyukaksoy</givenName>
      <familyName>Kaplan</familyName>
      <affiliation>TUBITAK BILGEM, Inst Informat Technol, TR-41470 Gebze, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Lana, Adnan</creatorName>
      <givenName>Adnan</givenName>
      <familyName>Lana</familyName>
      <affiliation>TUBITAK BILGEM, Inst Informat Technol, TR-41470 Gebze, Turkey</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Comparison Of Proposed Target Tracking Algorithm, Grnn Alpha, To Kalman Filter In 3D Environment</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2013</publicationYear>
  <dates>
    <date dateType="Issued">2013-01-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Conference paper</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/91445</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.81043/aperta.91444</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.81043/aperta.91445</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>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">In this study, the method we proposed GRNN alpha which is the specialized General Regression Neural Network (GRNN) algorithm, was used for estimating the target position in 3 Dimensional (3D) measurement environment. Although GRNN has only been used for estimating target velocity, GRNN alpha has the capability of estimating target's position as successful as the well known Kalman Filter (KF) algorithm. The performances of the mentioned algorithms are compared using simulated take-off and landing routes of aircrafts.</description>
  </descriptions>
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