Automation Workflow for Pre- and Post-Maneuver Trajectory Validation

This workflow directly addresses the high-stakes operational bottleneck of manually verifying maneuver plans and outcomes, a process prone to human error and time pressure. By automating pre-maneuver 'what-if' simulations against the latest debris catalog and post-maneuver telemetry comparison, it creates a defensible audit trail for regulators and insurers while preventing mission degradation from unsafe or poorly executed burns. The business value lies in risk reduction, operational throughput, and liability protection.

Implementation integrates high-fidelity propagators like Orekit or GMAT with conjunction data message (CDM) streams, satellite telemetry systems, and human review dashboards. The architecture requires robust exception routing for simulation failures or telemetry mismatches, and immutable logging for every validation step to satisfy compliance needs. This turns a reactive, manual verification process into a continuous, automated assurance layer embedded within the mission control loop.

This workflow automates the safety verification of planned maneuvers and confirms their successful execution, directly reducing the risk of creating new debris or mission loss. It eliminates the manual, error-prone process of running 'what-if' simulations against the debris catalog and comparing telemetry to predicted states. The operational upside comes from compressing validation cycles from hours to minutes, ensuring fuel is spent only on safe maneuvers, and creating an immutable record for liability and compliance purposes, which is critical for insurance and regulatory reporting.

Implementation integrates with Mission Control Systems (MCS) like AGI's STK or internally built ops software, and SSA data sources via APIs. The pre-maneuver agent uses high-fidelity propagators (e.g., Orekit, GMAT) for simulation. The post-maneuver agent compares achieved state vectors against predictions, flagging deviations for immediate investigation. Controls include mandatory human-in-the-loop approval for high-risk maneuvers or anomalies, with all data, decisions, and telemetry logged to a blockchain-like ledger for auditability. Rollout requires phased testing in a digital twin environment before operational deployment.

This workflow automates the critical, repetitive validation tasks that satellite operators must perform before and after every collision avoidance maneuver. Pre-maneuver, it ingests the planned delta-V and runs high-fidelity 'what-if' simulations against the latest debris catalog using propagators like Orekit or FreeFlyer, quantifying residual risk and flagging potential new conjunctions. Post-maneuver, it compares actual telemetry from the satellite bus against the predicted state, automatically detecting execution errors or off-nominal performance. The operational upside is a 90% reduction in manual analysis time, elimination of human calculation errors, and a continuous compliance record that satisfies stringent regulatory and insurance reporting requirements.

Implementation integrates with mission control systems (e.g., AGI STK, NASA GMAT), satellite telemetry pipelines, and regulatory databases. The architecture is built on an agentic framework like LangGraph, where specialized agents handle propagation, scoring, and reporting, coordinated by a central orchestrator that manages state and exception routing. Controls include mandatory human approval for high-risk maneuvers, confidence thresholds for automated validation, and immutable logging to a system like Splunk or Datadog for full observability. Rollout requires phased deployment, starting with non-critical assets, and rigorous simulation-based testing against historical conjunction events.

Rollout begins with a shadow-mode deployment, where the validation workflow runs in parallel with existing manual processes without commanding the satellite. This phase builds confidence in the AI's pre-maneuver 'what-if' simulations against the USSPACECOM catalog and its post-maneuver telemetry comparisons. Governance is enforced through immutable logging in a system like Splunk or Datadog, capturing every input ephemeris, probability score, and validation outcome to create a defensible audit trail for regulators (FCC, NOAA) and insurers.

A phased command-and-control handoff follows, starting with low-risk satellites in stable orbits. Human-in-the-loop approval gates remain mandatory for all maneuver authorizations, with the system escalating any validation failure or confidence-score threshold breach. Final rollout integrates the workflow directly with the flight dynamics system and mission planning software (e.g., AGI's STK, Analytical Graphics), automating the generation of command sequences and updating the satellite's planned mission timeline after a successful, validated maneuver.