Browsing by Subject "Finite difference time domain"

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    FDTD simulations of multiple GPR systems
    (IEEE, 2003-06) Oǧuz, Uğur; Gürel, Levent
    A multiple-GPR detection system was simulated. The main advantage of such a system was that it saves time by detecting both the transverse and the longitudinal positions of the target by a B-scan measurement, whereas the same detection can be achieved by a C-scan with a single-GPR system. Finite-domain time-difference (FDTD) method was employed to perform the simulations, in which the ground was homogeneous and the target was perfectly conducting.
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    Indoor localization with transfer learning
    (IEEE, 2022-08-29) Korkmaz, İlter Onat; Özateş, Tuna; Koç, Enes; Aydın, Ege; Kor, Ege; Dilek, Doğaç; Güngen, Murat Alp; Köse, İdil Gökalp; Akman, Çağlar
    Indoor positioning methods aim to estimate positions of transmitters where the GPS signals are unavailable. These systems usually employ algorithms explicitly trained for a single location such as fingerprinting method. For that reason, they can only be used in a particular location. This restriction prevents the use of the fingerprint method in tasks such as search and rescue operations where there is no prior knowledge of the place. A fingerprinting system using a trained algorithm with data collected from many places can work in multiple places. This paper proposes an indoor positioning system that uses the parameters of a pre-trained neural network trained with the data obtained from finite difference time domain simulations with transfer learning without collecting large amounts of data. The initial parameters for the model to be trained with the received signal strength (RSS) data collected from real places are used as be the parameters of the artificial neural network trained with the aforementioned simulation data. Performance results of the trained model are comparable to the results of the works in which fingerprinting method is employed in a single environment.