Improve Space Catalog Maintenance With Optimized Tasking

Heimdall optimizes SSA/SDA sensor tasking using advanced scheduling algorithms to improve space object catalog maintenance. Heimdall schedules ground-based and space-based sensors intelligently, applying predicted track accuracy, probability of detection, and Figure-of-Merit metrics to drive observations based on Information Gain and catalog error reduction. Optimized scheduling allocates sensors more effectively than manual tasking, resulting in improved accuracy and completeness of the space object catalog.

Heimdall applies advanced metrics—predicted track accuracy, probability of detection, and catalog-specific Figure-of-Merit calculations—to score observation opportunities and schedule sensors optimally. Manual scheduling focuses on basic availability checks without optimization metrics. Intelligent optimization drives tasking decisions based on Information Gain and catalog improvement goals like reducing estimated error covariance, enabling better resource allocation than manual availability-based assignment.

Heimdall schedules ground-based and space-based SSA/SDA sensors with configurable sensor attributes and custom slew-path optimization accommodating sensor-specific constraints. Dashboard configures sensors individually enabling scheduling diverse sensor types with different capabilities and constraints. Unified scheduling coordinates all available sensors—ground stations, space-based platforms, and specialized collection assets—enabling optimized observation allocation across heterogeneous networks.

Heimdall generates new tasking schedules responding to newly detected objects, object activity changes, and sensor anomalies in seconds or minutes instead of waiting until next day’s manual scheduling cycle. Manual tasking delays critical observations forcing operators to wait for scheduled planning phases. Event-driven tasking enables immediate sensor response to emerging situations—addressing new threats or unexpected activity in real-time where manual coordination creates dangerous operational delays.

Yes. Heimdall schedules ground-based and space-based sensors together using custom slew-path optimization and sensor-specific constraints enabling coordinated multi-platform tasking. Manual coordination treats ground and space sensors separately forcing operators managing different systems missing efficiency gains from integrated scheduling. Coordinated optimization allocates observations to optimal platforms—whether ground station or space-based asset—considering capabilities, constraints, and geometry enabling observation efficiency impossible with separated systems.

Heimdall automates optimization scoring and scheduling enabling responses in minutes versus hours for manual tasking while applying advanced metrics manual processes ignore. Manual tasking requires operators checking sensor availability, coordinating windows, seeking approvals and consuming hours per planning cycle. Optimized scheduling applies track accuracy, probability of detection, and Information Gain metrics enabling better resource allocation and faster response to events where manual coordination creates bottlenecks and delays.

Heimdall uses SSA/SDA-specific Figure-of-Merit calculations to score observations and guide tasking decisions based on catalog improvement metrics like reduced error covariance. Figure-of-Merit evaluates which observations contribute most to catalog quality considering track uncertainty, object importance, and observation value. Metric-driven tasking allocates sensors to observations improving overall catalog rather than assigning based only on basic availability enabling better catalog maintenance outcomes.

Yes. Heimdall has been deployed in secured environments for U.S. government customers with multiple years of successful operational heritage. Heimdall is part of the Deep Space Advanced Radar Capability (DARC) program and was deployed at the National Space Defense Center (NSDC), undergoing multiple upgrade cycles based on operator feedback under Air Force SBIR contracts. Operational heritage with continuous improvement cycles demonstrates a trusted system refined through real-world experience, not theoretical capability.

Heimdall algorithms are benchmarked against theoretically optimal sensor schedules in representative SSA/SDA scenarios building trust in optimization performance. Auria and academic partners continuously refine algorithms based on benchmarking results driving improvement and validating that optimization delivers near-optimal performance. Structured validation and continuous improvement ensure algorithms remain state-of-the-art while operator feedback cycles identify enhancements addressing real-world operational needs.

Heimdall is deployed for the Deep Space Advanced Radar Capability (DARC) program and other U.S. government Space Domain Awareness operations including deployment at the National Space Defense Center (NSDC). Air Force SBIR contracts support ongoing development and operational improvements. Government space surveillance programs leverage Heimdall for optimized sensor scheduling improving space object catalog maintenance and enabling faster response to emerging space threats.