Zoran Stanković, Nebojša Dončov

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Neural model capable to accurately and efficiently predict a propagation delay of electromagnetic signal in the ionosphere is proposed in this paper. The model performs this prediction for a given geographic location in Europe between 40° (N) and 70° (N) latitude and 10° (W) and 30° (E) longitude, according to the following parameters: particular day in a year, time during the day and frequency of a signal carrier. Architecture of the model consists of four multilayer perceptron (MLP) networks with the task to estimate, for the known values of the previously mentioned input parameters of the model, the approximate value of free ions concentration in the atmosphere along the signal propagation path above the geographic location of the receiver. Based on the estimated ions concentration and taking into account the considered frequency of the signal carrier, the model calculates the time delay of signal propagation in the ionosphere. The developed neural model is applicable on the whole territory of Republic of Serbia, for all four weather seasons in the period of low solar activity. The results of using the proposed model for the prediction of time delay of the GPS (Global Positioning System) signal in the area of city of Niš are provided in the paper.


neural networks, neural model, ionosphere, total electron content, signal delay estimation, global positioning system

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