Multi-Source Navigation Data Fusion Based on Factor Graph for Unmanned Helicopter Under Atmospheric Disturbance

Abstract

AbstractUnmanned helicopter has unique flight performance and plays an important role in the field of military and civil. Strong atmospheric disturbance environment is the comprehensive wind which has the effect on the body of the unmanned helicopter. Relying on the key project of NSFC (61533008), the research of the navigation interference and the state estimation method of the unmanned helicopter caused by strong airflow are focused in this paper. In view of the fact that only the inertial navigation system is difficult to meet the reliability and accuracy requirements of the unmanned helicopter navigation system in the strong airflow environment, a multi-sensor integrated navigation method based on the frame of factor graph is proposed in this paper. The performance of the integrated navigation system of the unmanned helicopter in the strong airflow environment can be effectively improved by using the factor graph filtering method. At the end of the paper, the simulation platform is built, and the algorithm proposed in the article is experimented by the simulation system. Then we analyzed the result and got the conclusion. The results show that the algorithm is helpful to solve the problem of navigation system fault caused by error increasing of navigation sensor of the unmanned aerial helicopter in the strong airflow interference environment.KeywordsUnmanned helicopterNavigationFactor graphAtmospheric disturbance