Atilla Saadat, Turion Space Corporation; Vince Chen, Turion Space Corporation; James Austin, Turion Space Corporation
Keywords: Space Situational Awareness, Space Domain Awareness, RSO Imaging, Spacecraft Attitude Optimization, Autonomous Mission Planning, On-Orbit Commissioning, Satellite Dynamics, Imaging Precision, Target Tracking, Collision Avoidance
Abstract:
In the realm of Space Situational Awareness (SSA) and Space Domain Awareness (SDA), accurately imaging Resident Space Objects (RSOs) is essential for precise orbit determination, collision avoidance, assisting third-party on-orbit commissioning, and sustainable space operations. This research introduces a novel methodology for spacecraft attitude optimization and autonomous mission planning tailored for RSO imaging with a space-based asset. The approach integrates advanced optimization algorithms with stringent operational constraints to generate high-fidelity imaging opportunities for RSOs, identified by their Norad IDs, within a predetermined temporal window.
The primary objective of this work is to develop and validate an end-to-end automated system that efficiently schedules imaging missions and optimizes customer tasking. The system computes optimal imaging opportunities by analyzing a comprehensive set of metrics, including relative in-plane velocity, imager exposure times, pixel occupancy, illumination factor, relative distance, probability of capture, imager Sun exclusion constraints, and blurring effects. These metrics collectively determine the most favorable conditions under which a spacecraft’s imaging sensor can acquire high-quality images. By identifying the optimal imaging window for each RSO, the system ensures that the generated imaging commands maximize data quality and operational efficiency, ultimately delivering images with the highest pixel occupancies and minimal blur.
A critical component of the methodology is the incorporation of operational constraints inherent in spacecraft dynamics. The optimization process is specifically designed to minimize star tracker exclusion zones—areas influenced by the Sun and Earth—to ensure that the Attitude Determination and Control Subsystem (ADCS) maintains optimal performance while preserving the spacecraft’s operational lifetime. This integrated approach not only improves ADCS pointing accuracy but also reduces the risk of operational anomalies during imaging, thereby supporting both the mission’s technical objectives and customer requirements.
The developed software is engineered with a modular architecture, allowing seamless integration with various satellite system configurations, including different imagers, star trackers, and orbital regimes. This adaptability ensures that the system is both scalable and versatile, making it applicable to a wide range of satellite platforms and mission profiles. Additionally, the mission planning component is designed to incorporate customer tasking requirements by optimizing the scheduling of imaging operations based on real-time priorities and the most favorable imaging conditions.
The proposed methodology underwent rigorous validation using both third-party spacecraft dynamics simulation software and on-orbit demonstrations with Turion Space’s Droid.001 spacecraft. In these tests, the system was verified to perform with inertial pointing imaging, successfully capturing several RSO images of varying sizes and ranges under diverse operational conditions. Building on this success, the system will soon be tested on-orbit with Droid.002, which is equipped with advanced target tracking capabilities to enhance imaging precision and quality further
The outcomes of this research are multifaceted. By enabling autonomous optimization of spacecraft attitude for space-based RSO imaging and integrating dynamic customer tasking, the proposed system can significantly enhance orbit determination precision, support effective space traffic management, minimize collision risks, and assist in third-party on-orbit commissioning. Its end-to-end mission planning seamlessly aligns RSO image tasking with dynamic calculations, optimizing throughput and ensuring that the optimal set of imaging targets is captured within the available timeline. Furthermore, automation-driven operational efficiencies reduce the need for manual intervention, leading to lower operational costs and extended mission lifespans. The system’s robust, modular design positions it as a critical technology for a diverse range of stakeholders in the SSA/SDA domain, including government agencies and commercial operators.
The work presented not only pushes the boundaries of automated mission planning but also demonstrates tangible, real-world performance improvements through on-orbit validations. This research represents a significant advancement in the field, promising to deliver safer, more efficient, and sustainable space operations.
Date of Conference: September 16-19, 2025
Track: Space-Based Assets