Autonomous navigation method based on federated Kalman filter for lunar rover

It is essential for lunar rover to know its position in order to fulfill the lunar exploration mission. So the autonomous navigation method for lunar rover has become an important topic. In this paper, a new autonomous navigation method for lunar rover based on federated Kalman filter was described. The principle of this method was introduced, and the system equation for lunar rover based on the rover motion model was developed. Then the celestial navigation subsystem based on the measurement coming from sun sensor and the DR navigation subsystem based on the measurement coming from velocity gyro and odometer were presented. And the federated Kalman filter was used to implement optimization estimation and information fusion in this method. Finally, the simulation of this method was finished. A simulation results demonstrated that this method has higher precision of position and head angle. Another simulation results demonstrated the reliability, fault tolerance and feasibility of this method.