Debris-Aware Ground Station Pass Scheduling Automation

This component continuously ingests and normalizes Conjunction Data Messages (CDMs) from sources like SOCRATES, CARA, or commercial SSA providers. It filters false positives using ML models and orbital covariance analysis, then maps high-probability conjunction events to specific satellites and their scheduled ground passes. The system tags any pass that overlaps with a high-risk conjunction window or the immediate post-maneuver stabilization period, preventing the scheduling of critical operations during these times.

The core scheduling agent evaluates pass requests against a weighted model of constraints: 1) Risk: Conjunction and post-maneuver blackout periods. 2) Priority: Mission-critical command uploads vs. routine telemetry downlinks. 3) Resource: Ground station availability and visibility windows. 4) Efficiency: Minimizing pass fragmentation. Using constraint-satisfaction algorithms, it generates an optimized schedule that maximizes data return while adhering to all safety and operational guardrails.

This agent integrates directly with satellite telemetry and mission planning systems. It consumes planned maneuver schedules and real-time health status (e.g., attitude control stability, power levels). After a maneuver, it automatically imposes a configurable lock-out period on scheduling high-priority passes, allowing time for telemetry validation and subsystem re-stabilization. This prevents scheduling a crucial command pass when the satellite is in an anomalous or recovering state.

When a new high-priority conjunction alert is received or a maneuver is executed, this orchestration layer triggers an automatic re-scheduling cycle. It identifies all impacted passes, calculates alternative slots (e.g., shifting to a different ground station or time), and resolves conflicts using predefined business rules. The agent presents change proposals to human operators for approval, along with a clear impact assessment on data return and mission timelines.

The final component is the integration layer that translates the approved schedule into executable actions. It generates standardized pass scripts (e.g., in JSON or XML format) compatible with ground station automation software like TSOPS or commercial systems. It includes verification steps to confirm antenna pointing, link acquisition, and command authority before the pass begins, and feeds pass performance data (e.g., data volume, bit error rate) back into the system for continuous optimization.

Every scheduling decision—pass approval, rejection, or re-allocation—is logged with a complete audit trail. This includes the conjunction risk data considered, the optimization logic applied, any human overrides, and the final outcome. This component automatically generates reports for internal review and regulatory compliance (e.g., demonstrating due diligence in protecting space assets), creating a defensible record for insurers and stakeholders.

The workflow ingests real-time conjunction data messages (CDMs) and ephemerides from sources like Space-Track, commercial SSA providers, or internal fusion engines via secure APIs. This provides the foundational risk signal—identifying when and where a satellite will be in close proximity to debris—that the scheduler must avoid. Integration requires normalizing disparate data formats and applying confidence filters to prevent false-positive alerts from disrupting operations.

Core scheduling logic integrates directly with the operator's mission planning or flight dynamics system (e.g., AGI's STK, internally developed tools). This bidirectional link allows the scheduler to query planned payload activities (e.g., critical imaging windows) and push updated pass schedules that account for maneuver blackout periods or high-risk intervals. The architecture must preserve the system-of-record's authority while injecting risk-aware constraints.

Direct integration with ground station management software (e.g., KSAT Lite, AWS Ground Station, custom network ops) is non-negotiable. The workflow agent must have read/write access to the pass booking system to block or modify requests during high-risk periods and to re-allocate antenna time dynamically. This requires robust exception handling for booked passes that must be moved, including automated stakeholder notification protocols.

To avoid scheduling passes during anomalous post-maneuver states, the scheduler ingests real-time telemetry streams. Integration with platforms like NASA's TETRA or custom M&C systems allows the agent to check subsystem status (e.g., attitude stability, thermal regime) before releasing a pass for command upload. This prevents sending commands to a satellite that is not ready to receive them, protecting mission safety.

Tight coupling with the fuel-aware maneuver recommendation workflow is critical. The scheduler consumes the planned maneuver timeline—including pre-burn calibration and post-burn stabilization windows—to automatically embargo ground contacts. This integration ensures the satellite is in a known, stable state for communication, turning what is often a manual coordination task into a deterministic, automated constraint.

The core integration fabric is a custom orchestration layer, built with tools like LangGraph or Temporal, that sequences agents, manages state, and enforces business rules. It connects all above systems via APIs and emits structured logs to an observability platform (e.g., Datadog, Grafana). This provides end-to-end traceability for every scheduling decision, a requirement for audit trails and operational debugging.