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 / DI LECCE, Vincenzo; Amato, A.; Piuri, V.. - (2008), pp. 4-8. (Intervento presentato al convegno International Conference on Computational Intelligence for Measurement Systems and Applications, IEEE CIMSA 2008 tenutosi a Istanbul, Turkey nel 14-16 July 2008) [10.1109/CIMSA.2008.4595822].
Neural technologies for increasing the GPS position accuracy
DI LECCE, Vincenzo;
2008-01-01
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
