A novel fast and accurate algorithm for Terrain Referenced UAV localization

Recently, unmanned aerial vehicles (UAVs) have become one of the most popular and promising means for both military and civilian posts and academic research areas. Localization of the UAVs and persistent tracking of a UAV have vital importance to provide a UAV with navigation information and help to cope with getting lost permanently. Indeed, Inertial Navigation System (INS) and Global Positioning System (GPS) seem to be adequate for navigation of UAVs. However, an alternative augmented navigation system for UAVs should be taken into consideration since INS has accumulated errors and GPS always has the possibility of jamming and satellite signal loss. Terrain Referenced Navigation (TRN) could be a good alternative as a decision support system for these main systems. This study aims to detect the location of a lost or GPS-disabled UAV throughout a planned flight by using only the terrain data. In addition, assumptions and limitations are minimized for the sake of simplifying the process to apply this methodology on a real UAV in the future, e.g. flight through all directions with physically possible turn rates is allowed. In order to provide data of the terrain, Digital Elevation Model (DEM) of the flight region with 30m resolution is exploited. The proposed method is based on searching and matching the collected elevation values of the terrain below UAV within the DEM and makes use of simulation techniques to test the accuracy and performance. The whole algorithm utilizes a sequence of elevation values with a predefined length (i.e. profile). Mainly, all possible profiles are generated before the flight and stored in a huge search space. We identify, sort and classify these elevation profiles in order to perform search operations in a small subset of the huge set. During the flight, a sequence of terrain elevations, which is computed with the help of radar and barometric altimeter measurements, is searched within a small neighborhood of corresponding profile set.