Effective Cooperative UAV Searching Using Adaptive STGM Mobility Model in a FANET

Abstract

Flying Ad-Hoc Network (FANET) is a special type of Mobile Ad-Hoc Network (MANET) consisted of a swarm of Unmanned Aerial Vehicles(UAVs). Mission planning for effective cooperative UAV searching must take into account the connectivity of UAVs for information sharing among UAVs in the FANET. Traditional mission planning usually uses predefined routes or use simple mobility models to generate the trajectories of UAVs, which do not take network connectivity as an important factor for high-quality cooperative searching. On the other hand, many innovative FANET mobility models have been investigated only for FANET simulation. In this paper, we propose a framework applying a recent group mobility model to mission planning with consideration on the network connectivity. For this purpose, we extend the Spatiotemporally Correlated Group Mobility Model (STGM) with adaptivity on its parameters that decide the spatial or temporal correlations among UAVs. Next, we introduce an area information coverage metric to evaluate the quality of mission planning enhanced by this adaptive mobility model. Finally, an algorithm is designed to optimize the metric. The experimental results show that our framework gains impressive improvements on effective information collection by the UAV swarm.