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http://dx.doi.org/10.12673/jant.2018.22.5.409

Performance Analysis of Artificial Neural Network for Expanding the Ionospheric Correction Coverage of GNSS  

Ryu, Gyeong-don (Weapon System Engineering, University of Science and Technology)
So, Hyoungmin (Agency for Defense Development)
Park, Heung-won (Agency for Defense Development)
Publication Information
Journal of Advanced Navigation Technology / v.22, no.5, 2018 , pp. 409-414 More about this Journal
Abstract
Extrapolating the correction information of ionosphere is essential for expanding wide area differential GPS (WADGPS) service area beyond the reference station network. In this paper, design and analysis of the artificial neural network for expanding the ionospheric correction region will be proposed. First, analysis about influence of each input of neural network were performed. The inputs are the day/year periodic function, sunspot number, and geomagnetic index (Ap). Second, performance analysis with respect to the number of hidden layers and neurons in the neural network is shown. As a result, estimation of total electron contents (TEC) on the high/low latitude regions in solar max(2014) are displayed.
Keywords
GNSS; Ionosphere; Neural network; Extrapolation;
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Times Cited By KSCI : 1  (Citation Analysis)
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