DocumentCode
2526772
Title
Neural technologies for increasing the GPS position accuracy
Author
Lecce, V. Di ; Amato, A. ; Piuri, V.
Author_Institution
DIASS, Politec. di Bari, Bari
fYear
2008
fDate
14-16 July 2008
Firstpage
4
Lastpage
8
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.
Keywords
Global Positioning System; learning (artificial intelligence); neural nets; radio receivers; telecommunication computing; GPS receiver position accuracy; neural network training; Clocks; Computational intelligence; Extraterrestrial measurements; Global Positioning System; Information technology; Neural networks; Position measurement; Satellite broadcasting; Satellite navigation systems; US Department of Defense; GPS position accuracy; neural network;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence for Measurement Systems and Applications, 2008. CIMSA 2008. 2008 IEEE International Conference on
Conference_Location
Istanbul
Print_ISBN
978-1-4244-2305-7
Electronic_ISBN
978-1-4244-2306-4
Type
conf
DOI
10.1109/CIMSA.2008.4595822
Filename
4595822
Link To Document