Precise Positioning Method of Unmanned Aerial Vehicle in Enclosed Environments by Integrating Multi-Sensor Information: Application of a Kalman Filter and Particle Filter Fusion Model Based on Dynamic Environment Adaptation

Today's article comes from the IEEE Access journal. The authors are Zhang et al., from Xihang University, in China. In this paper, they're proposing a new positioning method for indoor UAVs that fuses information from multiple sensors and dynamically adapts how that information is used.

DOI: 10.1109/ACCESS.2025.3641189