1 Ocak 2010 Konferans bildirisi Açık Erişim

Yoldemir, Ahmet Burak; Sezgin, Mehmet

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    <subfield code="a">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.</subfield>
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    <subfield code="a">Real-time Buried Object Detection Using LMMSE Estimation</subfield>
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