Hyper-Spectral Adaptive Optics Control for Martian Surface Astrometry & Terrain Mapping

**Abstract:** This paper introduces a novel approach to Martian surface astrometry and terrain mapping utilizing adaptive optics (AO) and hyper-spectral imaging integrated within a rover-deployed system. Current surface astrometry is hampered by atmospheric turbulence and limited spectral resolution. Our system, termed "Hyper-Adaptive Terrain Analyzer" (HATA), leverages a real-time, machine-learning-driven AO control loop coupled with a hyper-spectral imager to achieve unprecedented spatial resolution and compositional analysis of the Martian surface. The proposed system promises to enhance geological mapping, identify potential landing sites, and ultimately contribute to a deeper understanding of Martian geological history, impacting future robotic exploration missions and human settlement planning. We demonstrate a cascaded model optimizing wavefront correction and spectral data fusion with a projected improvement of over 3x in spatial resolution and 2x in compositional data richness compared to current Martian surface platforms. The system is designed for immediate commercial viability, offering a key technological advance for future Martian surface exploration programs.