UAV cluster geometric information fusion cooperative positioning algorithm with LEO satellite system

Abstract

With the rapid development of unmanned aerial vehicle (UAV) clusters, they will become the main means in urban transportation, traffic monitoring and other fields. The positioning accuracy of UAV clusters is the core basis of the application, this paper proposes a UAV cluster information geometry fusion positioning method based on low-orbit satellite system, which uses the geometric relationship between UAV clusters to transform the low-orbit constellation navigation information of each UAV into an information geometry probability model, reducing the influence of the low-orbit satellite system time asynchrony, and through Kullback–Leibler average fusion to achieve UAV cluster real-time high-precision positioning. The method effectively solves the problem caused by the easy loss of GNSS signals in the obscured environment, and significantly improves the reliability and stability of UAV cluster positioning in urban environments. Comparing the method of this paper with the existing UAV fusion navigation methods in terms of positioning accuracy stability, positioning real-time and error mutation under the occlusion scenario, the experimental results show that the method of this paper has obvious superiority in the above indexes.