An integrated celestial navigation scheme for spacecrafts based on an optical interferometer and an ultraviolet Earth sensor is presented in this paper. The optical interferometer is adopted to measure the change in inter-star angles due to stellar aberration, which provides information on the velocity of the spacecraft in the plane perpendicular to the direction of the observed star. In order to enhance the navigation performance, the measurements obtained from the ultraviolet Earth sensor is used to eliminate the unfavorable effect caused by the gravitational deflection of starlight. As the prior knowledge about the optical path delay bias of the optical interferometer may be ambiguous, a Q-learning extended Kalman filter is derived to fuse the two types of measurements, and estimate the kinematic state together with the optical path delay bias. The solution of the autonomous navigation system consists of position, velocity and attitude of the spacecraft. Numerical simulation shows that an evident improvement in navigation accuracy can be achieved by introducing the ultraviolet Earth sensor into the navigation system. In addition, it is shown that the Q-learning extended Kalman filter performs better than the traditional extended Kalman filter.
Q-Learning as Failure