The work presents the results of studies on dependence of effectiveness of chosen robust estimation methods from the internal reliability level of a geodetic network. The studies use computer-simulated observation systems, so it was possible to analyse many variants differing from each other in a planned way. Four methods of robust estimation have been chosen for the studies, differing substantially in the approach to weight modifications. For comparative reasons, the effectiveness studies have also been conducted for the very popular method in surveying practice, of gross error detection basing on LS estimation results, the so called iterative data snooping. The studies show that there is a relation between the level of network internal reliability and the effectiveness of robust estimation methods. In most cases, in which the observation contaminated by a gross error was characterized by a low index of internal reliability, the robust estimation led to results being essentially far from expectations.

The paper presents the results of investigating the effect of increase of observation correlations on detectability and identifiability of a single gross error, the outlier test sensitivity and also the response-based measures of internal reliability of networks. To reduce in a research a practically incomputable number of possible test options when considering all the non-diagonal elements of the correlation matrix as variables, its simplest representation was used being a matrix with all non-diagonal elements of equal values, termed uniform correlation. By raising the common correlation value incrementally, a sequence of matrix configurations could be obtained corresponding to the increasing level of observation correlations. For each of the measures characterizing the above mentioned features of network reliability the effect is presented in a diagram form as a function of the increasing level of observation correlations. The influence of observation correlations on sensitivity of the w -test for correlated observations (Förstner 1983,Teunissen 2006) is investigated in comparison with the original Baarda’s w -test designated for uncorrelated observations, to determine the character of expected sensitivity degradation of the latter when used for correlated observations. The correlation effects obtained for different reliability measures exhibit mutual consistency in a satisfactory extent. As a by-product of the analyses, a simple formula valid for any arbitrary correlation matrix is proposed for transforming the Baarda’s w -test statistics into the w -test statistics for correlated observations.

The study presents results of the internal reliability analysis of structural modules used for the determination of horizontal displacement in incomplete trigonometric network. The influence of such elements as: number of control points, sight line length and arrangement of control points around the instrument station on reliability was analysed. Furthermore the analysis of the influence of diversification of reliability indices calculated for individual observations on the detection efficiency of non-dislocated control points was performed. The presented numerical example illustrates the possibility of incorrect valuation of control point stability because of a large diversification of reliability indices. The summary contains recommendations from the point of view of internal reliability for optimal designing of structural modules in incomplete trigonometric networks.

The paper presents the results of the studies on the determination of the degree of dependence between the adjusted observations, on the basis of the levels of their coexistence in a network. An approximate model is proposed making it possible to estimate that dependence without the necessity to perform the adjustment procedure. This model can be applied in the procedures of gross error detection in observations. Additionally, a supplementary algorithm to determine the coexistence levels for the observations on the grounds of the matrix of coefficients in the observation equations is presented.