Comparison of Localization Algorithms for Unmanned Aerial Vehicles

Unmanned Aerial Vehicles (UAVs) are experiencing exponential growth these days. UAVs are used for multi purposes such as for security, photography, weather forecasting etc. The increase in number of UAVs are causing compromise to the personal privacy of people as well as threats to the privacy of confidential areas. Determining the exact location of these UAVs is important in many aspects. In this paper, several well-known localization techniques are compared. These techniques include received signal strength (RSS), angle of arrival (AoA), correlative interferometry and Watson-Watt method. These are compared on the basis of different parameters i.e. cost, efficiency, range, accuracy, energy consumption and hardware size. The comparison results show that correlative interferometry is the best available solution for UAV localization. Complexity of each algorithm is also computed. Watson-Watt and AoA has less computational complexities compared to other methods which is computed as O(n) for both algorithms.