Title of article
RTDGPS Implementation by Online Prediction of GPS Position Components Error Using GA-ANN Model
Author/Authors
رفان، محمد حسين نويسنده Shahid Rajaee Teacher Training University, Tehran, Iran Refan, M.H , دمشقي، عادل نويسنده Electrical and Computer Engineering Faculty, Shahid Rajaee Teacher Training University, Tehran, Iran Dameshghi, A
Issue Information
فصلنامه با شماره پیاپی 0 سال 2013
Pages
8
From page
43
To page
50
Abstract
If both Reference Station (RS) and navigational device in Differential
Global Positioning System (DGPS) receive signals from the same satellite,
RS Position Components Error (RPCE) can be used to compensate for
navigational device error. This research used hybrid method for RPCE
prediction which was collected by a low-cost GPS receiver. It is a
combination of Genetic Algorithm (GA) computing and Artificial Neural
Network (ANN). GA was used for weight optimization and RS and Mobile
Station (MS) were implemented by the software. The experimental
results demonstrated which GA-ANN had great approximation ability and
suitability in prediction; GA-ANNs predictionʹ RMS errors were less than
0.12 m. The simulation results with real data showed that position
componentsʹ RMS errors in MS were less than 0.51 m after RPCE
prediction.
Journal title
Journal of Electrical and Computer Engineering Innovations (JECEI)
Serial Year
2013
Journal title
Journal of Electrical and Computer Engineering Innovations (JECEI)
Record number
1366884
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