Abstract
The accuracy of global positioning system (GPS) is not so high because of errors. Therefore, the differential GPS (DGPS) which is based on the successive transmission of correction factors is often used. The main parts of the system are a reference station and a user one. In this paper, reference position components error (RPCE) factors are used for implementing the system. The theory of increasing the accuracy of this system is based on the fact that if the satellites used in both stations are the same, the sources and the values of position error would almost be close to each other in both stations as well. In order to compensate the processing delays of the reference station, the RPCE factors were predicted by using the hybrid auto regressive moving average neural network algorithm. Simulation results showed that the root mean square (RMS) error of the prediction algorithm is 0.22 m. Moreover, practical tests by hardware board revealed the RMS error of positioning system is 0.45 m.
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