Mohammad Hossein Refan - Faculty of Electrical and Computer Engineering, Shahid Rajaee Teacher Training University
Adel Dameshghi - Faculty of Electrical and Computer Engineering, Shahid Rajaee Teacher Training University
Mehrnoosh Kamarzarrin - Faculty of Electrical and Computer Engineering Shahid Beheshti University

This study applied Fuzzy Neural Network (FNN) model to predict Pseudo-range Corrections (PRC) that is important for Real Time Differential Global Positioning System (RTDGPS) accuracy. Online training for real-time prediction of the PRC enhances the continuity of service on the differential correction signals and therefore improves the positioning accuracy. With a given set of data, the fuzzy neural networks (FNN) can online predict the PRC precisely when the PRC signal is lost for a short period of time. The experiments show that the prediction total RMS errors are less than 0.23 meter.

RTDGPS-FNN- PRC- Prediction-RTCM