Research on Relative Positioning of Multi-UAV Based on Multi-sensor Fusion

While Global Navigation Satellite Systems (GNSS) are commonly used for multi-UAV relative positioning, their susceptibility to interference and jamming in complex environments presents a significant limitation. Addressing the challenge of outdoor UAV positioning under GNSS-denied conditions, this paper proposes a multi-sensor fusion approach for multi-UAV relative positioning. The method integrates existing ranging modules and near-infrared vision to design a robust relative positioning system. Furthermore, a positioning error return function for UAV clusters is established and utilized within a reinforcement learning framework for formation control. Experimental validation—including mobile platform landings, multi-UAV simulations, and dual-UAV positioning tests—demonstrates that the proposed method provides high-precision positioning information for drone swarms and is effective for multi-UAV formations.