Aim of this paper is to present a method to improve the accuracy of a GPS receiver. It is well known that there are many factors affecting the accuracy of a GPS receiver. In this work, the authors point out that many of these factors, considered in a given geographic area, have a certain periodicity. An important example of this kind of factors is the sky satellite position relative to receiver. The proposed method uses a neural network to correct the position computed by the receiver. The neural network is trained to learn the errors introduced into the measuring system by the cyclic phenomenon in the various hours of the day.
Neural technologies for increasing the GPS position accuracy / V. Di Lecce, A. Amato, V. Piuri - In: CIMSA 2008 : IEEE international conference on computational intelligence for measurement systems and applications : proceedings : 14-16 july 2008, Istanbul, TurkeyPiscataway : Institute of electrical and electronics engineers, 2008. - ISBN 978-1-4244-2305-7. - pp. 4-8 (( Intervento presentato al 6. convegno IEEE International Conference on Computational Intelligence for Measurement Systems and Applications tenutosi a Istanbul nel 2008.
Neural technologies for increasing the GPS position accuracy
A. AmatoSecondo
;V. PiuriUltimo
2008
Abstract
Aim of this paper is to present a method to improve the accuracy of a GPS receiver. It is well known that there are many factors affecting the accuracy of a GPS receiver. In this work, the authors point out that many of these factors, considered in a given geographic area, have a certain periodicity. An important example of this kind of factors is the sky satellite position relative to receiver. The proposed method uses a neural network to correct the position computed by the receiver. The neural network is trained to learn the errors introduced into the measuring system by the cyclic phenomenon in the various hours of the day.Pubblicazioni consigliate
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