Satellite Collection Scheduling With Redundancy for Occlusion Mitigation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional task assignment techniques for small satellite constellations do not effectively mitigate occlusions caused by environmental disturbances, leading to useless data collection and increased data volume, without considering redundancy in collection schedules.
Innovation Solution
A randomization-based redundant collection task scheduling algorithm that tessellates observation regions into sub-regions, computes collection opportunities, and generates a schedule using a randomized selection algorithm with a decay function to control redundancy, ensuring successful data collection despite occlusions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If redundancy is added to collection schedule to mitigate occlusions, then reliability of data collection is improved, but data volume and resource consumption increase
Solution Approach 1:
The patent applies partial redundancy by selectively adding backup collection tasks only for sub-regions that meet specific criteria (e.g., high occlusion risk, low collection probability). Instead of uniformly redundant scheduling across all regions, the system performs partial action only where necessary, thus improving reliability without proportionally increasing data volume across the entire constellation.
Solution Approach 2:
The system dynamically adjusts scheduling parameters including redundancy level, tessellation granularity, and selection thresholds based on real-time conditions such as occlusion probability, satellite positions, and data priorities. By changing these parameters adaptively, the system optimizes the balance between collection success rate and data volume transmission.
2Productivity
If conventional optimization techniques are used for task assignment, then productivity is improved, but tolerance to environmental disturbances deteriorates
Solution Approach 1:
The system performs preliminary actions by pre-computing multiple collection opportunities for each sub-region before final task assignment. It identifies backup collection tasks in advance and prepares redundancy schedules beforehand, allowing the system to quickly respond to environmental disturbances without compromising real-time productivity.
Solution Approach 2:
The patent segments the observation regions into multiple sub-regions and processes them independently through the randomized selection algorithm. This segmentation allows the system to apply different redundancy levels to different sub-regions based on their specific characteristics, improving overall disturbance tolerance while maintaining efficient task assignment through modular processing.
3Loss of energy
If randomized selection algorithm is used to control redundancy, then loss of resources is reduced, but complexity of scheduling increases
Solution Approach 1:
The patent replaces complex deterministic optimization mechanisms with a randomized selection algorithm that uses probabilistic methods to determine redundancy. Instead of solving complex constraint satisfaction problems, the system uses random sampling with acceptance criteria, significantly reducing computational complexity while still achieving effective resource allocation and minimizing waste.
Data Source
AI summary
The present disclosure addresses unresolved problems of task scheduling by adding redundancy in a collection task schedule generated by a ground control station. Embodiments of the present disclosure provide a randomization based redundant collection task scheduling for mitigating occlusions in sensing by small satellite constellations. The randomization based redundant collection task scheduling algorithm receives as input a set of region of observations tessellated into sub-regions, and then collection opportunities for each sub-region is computed based on satellite tracks data. Further, a sub-set of collection opportunities is determined from all the possible collection tasks for each sub-region to further generate the collection task schedule for each of the region of observation. Number of collections opportunities is controlled by a decay function which holds number of redundant collections to a bound, thereby increasing chance of good collection without investing too much resource in redundancy to mitigate occlusions.