Shadow-assisted tightly-coupled asteroid landing navigation with co-optimization of beacon errors

Autonomous landing on small celestial bodies poses significant challenges due to irregular surface geometry, weak gravity, and limited navigational observability. This paper presents a shadow-assisted visual-inertial navigation framework that enhances localization performance during descent by incorporating shadow geometry as an additional visual constraint into a tightly coupled nonlinear optimization process. A joint optimization strategy is introduced to simultaneously estimate navigation states and beacon map errors, effectively reducing the impact of beacon uncertainty. Additionally, an adaptive weighting mechanism is proposed to modulate the influence of visual features based on observation redundancy, improving convergence robustness. Adequate numerical simulations demonstrate that the proposed method significantly improves the accuracy and stability of position, velocity, and attitude estimation. These results support the framework's potential for enabling precise, autonomous landing in future small-body exploration missions.