AI-Enhanced Imaging Protocols for Autonomous Asteroid Observation and Orbital Characterization

This project develops a comprehensive Standard Operating Procedure (SOP) for a next-generation observatory camera system, integrating artificial intelligence to enhance the precision, efficiency, and autonomy of asteroid imaging. The SOP will incorporate real-time feedback loops, where AI continuously monitors image quality metrics (e.g., sharpness, signal-to-noise ratio) and dynamically adjusts camera parameters to optimize results. Additionally, anomaly detection algorithms will flag inconsistencies in calibration frames--such as flat fields and dark frames--that may indicate sensor degradation or misalignment, ensuring long-term system reliability.

On the operational side, the project will implement AI-assisted decision-making capabilities, including target prioritization based on orbital parameters and threat relevance, and autonomous scheduling of observations to maximize telescope usage under variable environmental conditions. These innovations directly support Army Modernization Priorities such as Air and Missile Defense, Assured Positioning, Navigation, and Timing (PNT), and Networked Operations, while contributing to Army Research Areas in Artificial Intelligence, Autonomy, and Quantum-enhanced sensing. The resulting SOP will serve as a user-friendly reference for both routine observations and specialized research missions, enabling rapid orbital analysis and characterization of spaceborne objects with defense relevance.