The stochastic modeling of GPS observations

In global positioning system (GPS) applications several error sources affect the observations. Tropospheric delay that occurs during the propagation of the wave through the troposphere and multipath taking place as a result of signal reflection are the most important error sources. Both errors increase as the satellite elevation cut-off angle decreases. Thus, in practice, observations over 15° -20° are used and therefore those distorted by the multipath and tropospheric delay effects are not taken into account. In this case, the accuracy required for many engineering applications is easily achieved. However, for high precision applications this accuracy may not be adequate. In particular, the accuracy of a height component obtained by GPS is quite low for high precision geodetic or non-geodetic applications. One way to overcome this problem is to introduce of new stochastic models that enable us to process low elevated GPS observations too. In this study, the applications of 2 stochastic models are presented. The results show that these models improve the coordinate solutions.