Relative Positioning Method for UAVs Based on Multi-Source Information Fusion

Abstract

To improve the accuracy and reliability of the relative positioning for unmanned aerial vehicles (UAVs), a relative positioning method based on multi-source information fusion is proposed. An integrated positioning scheme is constructed by the Beidou Navigation Satellite System (BDS) receivers, Global Positioning System (GPS) receivers, Vision-Based Navigation System (VisNav), and Inertial Navigation System (INS). The BDS pseudorange relative difference equation, the GPS relative difference equation, the relative line-of-sight vector equation, and the INS measurement equation are established, respectively. The least squared (LS) method is used to realize information fusion, and the Gauss-Newton method is used to iteratively solve the relative position results. Finally, numerical simulation and result analysis are conducted with different sensor configurations. Simulation results show that BDS/INS/GPS/VisNav relative positioning result is obviously better than that of INS/GPS, INS/VisNav, and INS/GPS/VisNav, and the proposed method reduces the relative positioning errors and has a higher accuracy and excellent robustness. The research result is suitable for application scenarios with high navigation accuracy requirement such as AAR and intelligent swarm formation control.