Modified attitude factor graph fusion method for unmanned helicopter under atmospheric disturbance

The Unmanned Aerial Helicopter (UAH) has attracted increasing attention in the military and civil areas with the unique flight performance. The significant impact on the attitude measurement performance of UAHs by the strong airflow disturbance is an essential factor threatening flight safety. To improve the attitude measurement performance of UAHs under atmospheric disturbance, an attitude fusion method over the factor graph is applied and provides the plug-and-play capability. Based on the relationship between position, velocity and attitude, a new attitude correction algorithm for the Modified Attitude Factor Graph Fusion (MAFGF) navigation method is designed and constructed through the fused position and velocity information. Finally, results of simulation and experiment are given to show the effectiveness of the proposed method.