Clique-Based Overlapping Community Detection in Centralized MDS Collaborative Localization

The UAV swarm technology has received widespread attention from various industries. The high-precision cooperative navigation system provides support and guarantee for improving the overall operational efficiency of the UAV swarm. Community detection plays an important role in identifying the structure and function of the swarm networks. In this paper, we proposed a novel overlapping community detection method, O-CPM, to reuse overlapping beacon nodes in centralized MDS collaborative positioning process. With the idea of cherish those nodes who located at the edge of the interference area, we designed a collaborative localization scheme based on clique-based community detection method and centralized MDS collaborative localization algorithm. This solution solves the problem of reasonable allocation of beacon node resources at the edge of the interference area, improves the overlap rate of beacon nodes between communities, and enhances the overall positioning accuracy of the UAV swarm. It also improves the informationization and intelligence level of navigation and positioning of the swarm as a whole. Four other community detection method are served as baseline method to conduct our simulation experiments. Simulation results show that, the O-CPM can greatly improve the positioning accuracy, and is suitable for the application of larue-scale UAV swarm.