Generic Angle of Arrival methods for indoor positioning are highly affected by specific antenna and environment scenarios through design impurities or multipathcomponent propagations. Here we acquired a large dataset of four different antenna designs in three different measurement environments with >140000 snapshots obtained from Bluetooth 5.1 receiver. Using the spatial power spectral densities of the PDDA angle of arrival algorithm as feature set for a small Random Forest model, we could show that angle estimation performances for all antennas in all measured environments were significantly improved (PDDA MAE >16 vs RF MAE < 3). Based on the small model size the proposed architecture can be implemented in microcontroller applications for super resolution angle of arrival applications.