This thesis studies algorithms to estimate an aircraft’s position with different information from various radio stations. Because aircrafts both civilian and military are heavily dependant on GNSS signals, it can be interfered from hostile sources. The aircraft shall then be able to navigate without the GNSS signals. This thesis focuses on three radio navigation systems, DME,VOR and TACAN. With the measurements from these three radio stations and measurements from the inertial navigation system one can estimate a position with an estimation filter. In this thesis two types of filters will be used, the linear Kalman filter and the Extended Kalman filter. The linear Kalman filter will be used when converting the TACAN measurements to a pseudo position and the Extended Kalman filter will be used for the DME,VOR and TACAN measurements. The results shows that the converted TACAN measurements and TACAN measurements estimates very well in both north and east direction. When using only DME measurements the filter estimates the position fairly well in the direction towards the station and poorly in the orthogonal direction. For the VOR measurements the filter estimates the position quite poorly in the direction of the radio station and well in the orthogonal direction. In conclusion the converted TACAN measurement and TACAN measurement algorithm can be used for navigation purposes by its own measurements. However, the DME and VOR measurement algorithms need to be combined or using multiple stations at different locations to get better estimates in both directions. All of the filter could use some better tuning to get the optimal filter, but it is not necessary.