The current study presents results on the structure of the continental crust in Scandinavia. The data assembled is obtained using more than 80 seismic stations deployed by an international collaboration between Danish, Norwegian, Swedish, German and British universities called ScanArray experiment during 2012-2016. Stations used for this study are deployed over the central part of Norway and Sweden between 60°N and 66°N. The research area consists of the Archaean Domain, the Palaoeproterozoic Svecofennian Domain and Caledonian Deformed Domain. All stations will be recovered during 2017. The results from teleseismic P-wave receiver functions for 15 stations show high contamination of the data with shallow reverberations masking the Moho at some stations. Possible explanation for such a high amplitude reverberations might be a strong discontinuity between Proterozoic basement rocks and Caledonian Nappe rocks. H-k stacking results show an agreement in the Moho depth with previous studies pointing to the depths of 35-48 km, however at some stations another discontinuity at the depth of 55 km is visible. In general the data are characterized by relatively high level of noise and small quantity of good waveforms corresponding to the earthquakes located within the required range of epicentral distance from the stations. To improve these preliminary results, we use receiver-based techniques, such as P-wave and S-wave joint inversion through adaptive simulated annealing algorithm (ASA), a transdimensional hierarchical Bayesian inversion and autocorrelation. The ASA method has a number of advantages; among them, both P- and S-wave receiver functions are inverted simultaneously and the solution is obtained without large computational cost. However, the method requires certain subjective choices to be made e.g. the number of layers in the inversion is predefined and a delay term must be defined for both P- and S-waves. The Bayesian approach helps avoid making subjective choices of parameterization and over-fitting the data due to a rigorous treatment of uncertainty (both the number of layers and the data noise in the inversion are treated as free parameters). The autocorrelation is an emerging method, which was found to complement the receiver functions method well in certain geological settings.