Automated Satellite Activity Prioritization for Scalable Fleet Control
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Solution Overview
Problem
Existing ground segment systems for satellite control are limited to one-to-one operations, requiring manual command issuance and lacking scalability and efficiency in managing large satellite fleets.
Innovation Solution
A satellite operations center (SOC) within a fleet operations ground segment (FOGS) that utilizes virtualization and containerization to dynamically manage and prioritize satellite activity tasks based on space environment context, satellite telemetry, and orbital data, enabling automated and scalable command issuance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual one-to-one satellite control is used, then operational simplicity is maintained, but productivity and scalability deteriorate when managing large satellite fleets
Solution Approach 1:
The system implements automated prioritization where the satellite operations center automatically evaluates mission critical variables, determines task priorities, and sequences satellite activities without manual intervention. The SOC autonomously manages the activity queue based on real-time space environment context and satellite telemetry data
Solution Approach 2:
The ground segment system is designed to handle multiple satellite types and various activity tasks through a unified automated prioritization framework. The system universally applies mission critical variable assessment across different satellites and task types, enabling scalable fleet management
2Productivity
If automated prioritization based on multiple mission critical variables is implemented, then productivity and task sequencing accuracy improve, but device complexity and computational requirements increase
Solution Approach 1:
The prioritization system segments the evaluation process into distinct mission critical variables (task urgency, space environment context, satellite telemetry status, contact window availability). Each variable is independently assessed and weighted, allowing modular computation and systematic task sequencing
Solution Approach 2:
The system dynamically changes priority parameters based on real-time conditions. Mission critical variables are continuously updated using space environment context data and satellite telemetry, causing task priorities to adjust automatically as operational conditions change
3Measurement precision
If real-time space environment context data and satellite telemetry are continuously monitored, then task prioritization accuracy improves, but energy consumption and data processing requirements increase
Solution Approach 1:
The system performs preliminary assessment of mission critical variables using pre-collected space environment context data and satellite telemetry. By evaluating priority indicators before contact windows occur, the system reduces the need for intensive real-time processing during critical communication periods
Data Source
AI summary
Systems and methods of the present disclosure may use a satellite operations center (SOC) to access an activity queue of satellite activity tasks in an activity buffer, each satellite activity task being associated with at least one satellite in a fleet. The SOC may determine mission critical variables associated with each satellite activity task based on space environment context data, satellite telemetry data, the position of each satellite, and the trajectory of each satellite. The SOC may determine, for each satellite activity task, using at least one statistical model, a prioritization tier based on the mission critical variables of each satellite activity task, and determine a satellite activity order defining an order of the satellite activity tasks based on the prioritization tier of each satellite activity task. The SOC may modify the activity buffer to order the satellite activity tasks in the activity queue according to the satellite activity order.