Satellite Constellation Scheduling via Communication Graph Optimization
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Solution Overview
Problem
Existing satellite constellation scheduling methods struggle to efficiently plan data capture and communication tasks, leading to suboptimal resource allocation and increased operational costs.
Innovation Solution
A method is developed to generate a points-of-interest plan using a communication graph, which is solved using a mixed integer linear programming (MILP) formulation. This approach optimizes satellite scheduling by determining the most efficient paths for data capture and communication within the satellite constellation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional satellite constellation scheduling methods are used, then the scheduling process is simpler to implement, but the resource allocation efficiency deteriorates and operational costs increase
Solution Approach 1:
The patent introduces a ground station as an intermediary node in the satellite constellation network. This ground station mediates data transmission between satellites, enabling optimized routing decisions. The intermediary facilitates efficient resource allocation by providing a central coordination point for data flow management, resolving the contradiction between simplicity and efficiency.
Solution Approach 2:
The patent transforms the scheduling problem from traditional time-based sequencing to a multi-dimensional optimization approach using mixed integer linear programming. By adding spatial dimensions (satellite positions, ground station locations) and resource dimensions (data flow, communication channels) to the scheduling model, the system achieves superior resource allocation efficiency while managing complexity through structured mathematical formulation.
2Productivity
If optimized scheduling paths are implemented, then data capture and communication efficiency improves, but computational complexity increases
Solution Approach 1:
The patent performs preliminary action by pre-calculating optimal scheduling paths using mixed integer linear programming before actual satellite operations. The communication graph is constructed and solved in advance to determine optimal data capture and transmission sequences. This preliminary optimization enables efficient real-time execution without requiring complex computational decisions during satellite operations.
Solution Approach 2:
The patent creates a virtual copy of the satellite constellation system in the form of a communication graph. This graphical model replicates the physical system's structure and relationships, allowing complex optimization calculations to be performed on the model rather than directly on the physical system. The copied representation enables sophisticated path optimization while keeping the actual satellite operations simple and deterministic.
Data Source
AI summary
For generating a points-of-interest plan, a method generates communication graph nodes for at least one satellite. The method calculates communication graph edges from the communication graph nodes, wherein the communication graph nodes and the communication graph edges comprise a communication graph. The method solves the communication graph to yield a communication plan. The method generates a points-of-interest plan from the communication plan.