The Attitude Adjustment of Multi-rotor Unmanned Aerial Vehicles Based on Information Fusion Analysis

Abstract

The navigation technology adopted by unmanned aerial vehicles (UAV) is the combination of the Global Positioning System (GPS) and the Inertial Navigation System (INS). The major navigation data are obtained through the integration of various sensor information. Therefore, information fusion technology is very important for an integrated navigation system, which has become the research direction of researchers. The research of information fusion technology mainly involves three aspects, i.e. model, information, and algorithm. The space model of Kalman filter in discrete time state was built; in addition, the Sage-Husa adaptive Kalman filter (SHAKF) algorithm was applied to the research on UAV navigation attitude. The results have shown that the improved SHAEKF algorithm can adjust the specific gravity of each sensor according to the actual situation. In summary, the SHAEKF algorithm is very suitable for the efficient information fusion of multi-rotor UAV.