The terrestrial measurements using Electronic Distance Measurement (EDM) have been widely done for different applications such as deformation monitoring and establishing geodetic networks. The calibration of the EDMs reflects the quality of the estimated parameters. In geodesy, least squares principle is mainly used for estimating parameters. The least square estimation is adversely affected by the systematic and non-systematic errors resulting in bias for the estimated parameters. In this study, to compare efficacy of different robust methods, the Monte Carlo simulation is applied to the EDM calibration as well as real experiments. The parameters without errors are obtained as a result of the used methodology. The methods given in this study are basically based on iteratively reweighted least squares and can be used for both parameter estimation and outlier diagnostics. This is of particular importance for calibrations of electromagnetic distance measurements using the Monte Carlo simulation and the measured test baselines. The results showed that one of the advantages of the used methodology is the improvement of the reliability of the estimated calibration parameters.