Enhancing positioning accuracy of GPS/INS system during GPS outages utilizing artificial neural network |
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Authors: | Burak H Kayg?s?z Aydan M Erkmen ?smet Erkmen |
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Affiliation: | (1) Defence Industries Research and Development Institute, The Scientific and Technical Research Council of Turkey, TüBİTAK-SAGE GKL Lab. ODTü Yerleskesi, Balgat/Ankara, 06531, Turkey;(2) Electrical and Electronics Engineering Department, Middle East Technical University, Ankara, Turkey |
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Abstract: | Integrated global positioning system and inertial navigation system (GPS/INS) have been extensively employed for navigation
purposes. However, low-grade GPS/INS systems generate erroneous navigation solutions in the absence of GPS signals and drift
very fast. We propose in this paper a novel method to integrate a low-grade GPS/INS with an artificial neural network (ANN)
structure. Our method is based on updating the INS in a Kalman filter structure using ANN during GPS outages. This study focuses
on the design, implementation and integration of such an ANN employing an optimum multilayer perceptron (MLP) structure with
relevant number of layers/perceptrons and an appropriate learning. As a result, a land test is conducted with the proposed
ANN + GPS/INS system and we here provide the system performance with the land trials. |
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Keywords: | Inertial navigation Global positioning system Strapdown Backpropagation neural network Kalman filter |
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