DGPS Correction Prediction Using Artificial Neural Networks

This paper focuses on modelling and predicting differential GPS corrections transmitted by marine radio-beacon systems using artificial neural networks. Various neural network structures with various training algorithms were examined, including Linear, Radial Biases, and Feedforward. Matlab Neural N...

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Bibliographic Details
Published in:Journal of navigation 2007-05, Vol.60 (2), p.291-301
Main Authors: Mohasseb, M., El-Rabbany, A., Abd El-Alim, O., Rashad, R.
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Data collection
Exact sciences and technology
Global positioning systems
GPS
Navigation systems
Neural networks
Radiolocalization and radionavigation
Telecommunications
Telecommunications and information theory
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Summary:This paper focuses on modelling and predicting differential GPS corrections transmitted by marine radio-beacon systems using artificial neural networks. Various neural network structures with various training algorithms were examined, including Linear, Radial Biases, and Feedforward. Matlab Neural Network toolbox is used for this purpose. Data sets used in building the model are the transmitted pseudorange corrections and broadcast navigation message. Model design is passed through several stages, namely data collection, preprocessing, model building, and finally model validation. It is found that feedforward neural network with automated regularization is the most suitable for our data. In training the neural network, different approaches are used to take advantage of the pseudorange corrections history while taking into account the required time for prediction and storage limitations. Three data structures are considered in training the neural network, namely all round, compound, and average. Of the various data structures examined, it is found that the average data structure is the most suitable. It is shown that the developed model is capable of predicting the differential correction with an accuracy level comparable to that of beacon-transmitted real-time DGPS correction.
ISSN:0373-4633
1469-7785
DOI:10.1017/S0373463307004158