A Novel Hybrid Path Planning Algorithm for Localization in Wireless Networks

In this paper, we consider the problem of designing an efficient hybrid path planning algorithm to maximize the localization accuracy and to minimize the energy cost represented by the length of the trajectory taken by an Unmanned Aerial Vehicle (UAV). An urban scenario affected by a disaster is considered in this work. It is likely that victims are located in groups (e.g, collapsed buildings) and the purpose of a UAV is to explore the area and to identify people in need. For that, fast and accurate localization is required. Our developed hybrid trajectories were compared with the state-of-the-art algorithms through extensive simulations. The obtained results indicate that for the same assumptions, the proposed Hybrid G trajectory reduces the path length in average by 42%, with the increase of relative localization error only by 6%, when compared to the best performing Double-Scan trajectory. Moreover, it ensures 99% of localized nodes in the area of size 160000 m2.