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Star-Fusion: A Multi-modal Transformer Architecture for Discrete Celestial Orientation via Spherical Topology
Reliable celestial attitude determination is a critical requirement for autonomous spacecraft navigation, yet traditional "Lost-in-Space" (LIS) algorithms often suffer from high computational overhead and sensitivity to sensor-induced noise. While deep learning has emerged as a promising alternative
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