Angular velocity current statistical model based real-time celestial navigation for lunar rover

The long-time, long-range autonomous navigation system is one of the key technologies which assist lunar rover to finish scientific exploration missions. A novel real-time celestial navigation (RCN) method is proposed to solve this problem, which is based on celestial observation and output of angular rate gyroscope. In this paper, the star´s direction vector from star sensor is treated as observation for system measurement equation; kinematics model is established using this angular velocity current statistical model (ACSM) for the rover, and its attitude quaternion differential equation is treated as system state equation. Finally, the extended Kalman filter (EKF) gives the solutions of rover´s position, heading and attitude. Simulation results show that this method could obtain higher celestial navigation accuracy in real-time.