Positioning Optimization Method Based on Satellite Spatiotemporal Information for Queqiao Constellation System

Due to the fact that the number of visible satellites is limited, the finiteness of observation information and the ill-condition of the observation equation seriously constrain the positioning accuracy of the Least Squares (LS) method. To address this, a spatiotemporal information-enhanced LS positioning optimization method for future Queqiao communication-navigation-remote sensing constellation was proposed, aiming to improve the robustness of LS-based solutions. First, an auxiliary equation incorporating multi-epoch pseudorange observations was constructed, coupled with a dynamic weighting strategy based on a constant-velocity motion model, to effectively utilize historical data and mitigate information deficiency in dynamic scenarios. Second, multi-epoch inter-satellite distance measurements are introduced to form geometric constraints that to suppress ill-conditioning in the observation model. Finally, a Forward-Backward Smoother (FBS) algorithm was applied to further refine positioning results and enhance solution stability. Simulation experiments based on platform-generated orbital data of the Queqiao constellation demonstrate that, under a 10 m orbital error and with a historical epoch length of 19, the proposed method—fusing multi-epoch pseudorange and inter-satellite distance data with FBS smoothing—achieved a positioning accuracy of 7.03 ± 2.50 m. Compared to the conventional LS method without any auxiliary information or smoothing, the positioning mean error was reduced by 88.26% and the standard deviation by 96.14%, providing solid technical support for high-precision positioning and navigation services required for Chinese astronauts' lunar surface operations.