Abstract: This paper focuses on the core issue of spacecraft autonomous navigation in deep space exploration. It systematically elaborates on the positioning principle based on celestial angle measurement navigation and the velocity measurement principle leveraging the aberration effect. On this basis, a loosely coupled architecture is adopted to solve for position and velocity separately, and a decoupled extended Kalman filter (EKF) is designed to achieve state fusion estimation. In terms of positioning, a vector geometric model involving the detector, stars, planets, and other celestial bodies is constructed, and the spacecraft’s position is solved using measurement data from a star sensor. In terms of velocity measurement, the relativistic aberration formula from special relativity is used to invert the three-dimensional velocity via changes in the line-of-sight direction of three or more stars. The navigation filter is designed based on spacecraft orbital dynamics, establishing a state equation that includes lunar gravity and perturbation forces, and state estimation is realized through a decoupled extended Kalman filter, which simplifies model complexity while ensuring accuracy. Simulation results show that, under high sensor accuracy, the position and velocity accuracy of a spacecraft orbiting the Moon can reach the order of hundreds of meters and sub-meter per second, respectively, providing a theoretical basis and engineering reference for the design and implementation of autonomous navigation systems for spacecraft.