On the consideration of combined measurement uncertainties in relation to GUM concepts in adjustment computations

Abstract

Abstract In this contribution it is shown how an extended uncertainty budget of the observations according to the Guide to the Expression of Uncertainty in Measurement (GUM) can be considered in adjustment computations. The extended uncertainty budget results from the combination of Type A standard uncertainties determined with statistical methods and Type B standard uncertainties derived with nonstatistical methods. Two solutions are investigated, namely the adjustment in the classical Gauss-Markov model and the adjustment in the Gauss-Markov model using Monte Carlo simulations for the consideration of the uncertainties of the observations. Numerical examples are given to show that an appropriate interpretation of the dispersion measures for the unknowns is particularly important in order to avoid misinterpretation of the results. Furthermore, the effects of changing the weights of the observations on the adjustment results are shown. Finally, practical advice for the consideration of an extended uncertainty budget of the observations in adjustment computations is given.