Estimation Algorithm For Autonomous Airborne Refueling Using An INS/GPS/Vision Integrated Relative Navigation System

Unmanned aerial vehicles are very suitable for the implementation of many special tasks due to their high mobility and low maintenance costs.But the limited fuel volume restricts their application.Aerial refueling technique can extend aircrafts' flight range,payload and endurance,which can solve the above problems effectively.The purpose of this thesis is to develop a state estimation system for the Autonomous Aerial Refueling(AAR)operation through an INS/DGPS/vision integrated navigation system.By applying the extended Kalman filtering and adaptive federated filtering,a three mode navigation algorithm is proposed according to the relative navigation scenario.Firstly,the stage estimation problem within an AAR specific scenario is parameterized and the relative kinematics between the tanker and the receiver aircraft is derived.The measurement models of gyroscope,accelerometer,GPS,monocular and stereoscopic vision are also analyzed and provided.To provide the accurate navigation output,a relative navigation filter based on extended Kalman filter(EKF)is designed for INS/GPS based and INS/Vision based relative navigation system respectively.The dynamic system model and measurement model are established.The Jacobian matrix and measurement matrix are also derived.In the premise of formation flight of the receiver and tanker,the performance of the EKF filter is evaluated.Aiming at the multi-sensor fusion problem,an adaptive federated filter is designed.The information distribution coefficient can be adjusted adaptively according to the covariance matrix and the measurement disturbance of each subsystem.The simulated results show that the modified federated filter can improve the precision of the integrated system effectively.Finally,an AAR simulation platform is established in the Matlab environment.The performance of the adaptive federated filter is evaluated in the simulated AAR scenario.A comparative analyses based on the adaptive federated filter and other filter is also made.