Hierarchical Collaborative Navigation Method for UAV Swarm

Unmanned aerial vehicle (UAV) swarm technology can expand the working scope of tasks and improve the overall task efficiency. Traditional single leader-follower fusion algorithms for cooperative navigation cannot fully utilize collaborative navigation information, and low reliability and navigation precision in interference cases. Meanwhile, the full connected fusion algorithm for cooperative navigation shows a large relative computing and communication burden and inflexibility to overcome the faults. Therefore, this paper proposes a collaborative navigation algorithm for a UAV swarm based on a hierarchical structure. A model for intervehicle collaborative measurement of UAV swarm cooperative navigation, with the line-of-sight calculation uncertainty estimation, is established. The hierarchical collaborative navigation fusion algorithm that could be adaptive to asynchronous updating of members in the swarm is designed. A comparison of simulation results of cooperative navigation of the UAV swarm by the different cooperative fusion algorithms is provided. The results indicate that the proposed method can improve the positioning accuracy and robustness of the cooperative navigation of a UAV swarm.

Automated summary

This paper proposes a collaborative navigation algorithm for a UAV swarm based on a hierarchical structure, which improves the positioning accuracy and robustness through collaborative measurement model and hierarchical fusion algorithm.