Distributed Filtering over Sensor Networks for Autonomous Navigation of UAVs

The paper studies the problem of autonomous navigation of a multi-UAV system with the use of the Unscented Information Filter (UIF) and the Distributed Particle Filter (DPF). It is considered that m UAV (helicopter) models are monitored by n different ground stations. At each monitoring station a filter is used to track each UAV by fusing measurements which are provided by various UAV sensors, while by fusing the state estimates from the distributed local filters an aggregate state estimate for each UAV is obtained. The UIF and DPF estimated state vector is in turn used by a flatness-based controller that makes the UAV follow the desirable trajectories.