ABSTRACT
The normally used procedure for the geodetic control network adjustment is the least squares method. Assuming that random measurement errors come from the normal probability distribution, estimates obtained using the least squares method are optimal (unbiased and efficient estimate). However, in real conditions, outliers may be part of a set of the measurements, such as the impact of a horizontal refraction. These outliers are causing a violation of the assumption of normality and, therefore, the estimates derived using least squares method lose their optimal properties. For high-quality processing of accurate geodetic control networks, it is necessary to detect outliers and reduce their influence on the resultant estimate using a suitable concept. In the submitted paper, a horizontal geodetic network based on the terrestrial measurements is processed using the least squares method with refraction model and the robust statistical methods. Chosen model of the estimation of horizontal refraction is based on the theoretical basis of defining refraction between two points and the occurrence of refractive blocks in a horizontal geodetic network. The results of experiments indicate that the most accurate results, thus the lowest incidence of the horizontal refraction, are permanent during cloudy weather. If the measurement is done during sunny weather, it is more appropriate to use the least squares method supplemented with a horizontal refraction model to process a horizontal geodetic network.
