Orbital Collision Screening Using Spatial Descriptors
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for orbital collision screening are inefficient due to the high computational requirements for accurately predicting the positions of artificial satellites and other space objects in near real-time, especially when dealing with a large number of objects in low-Earth orbit.
Innovation Solution
A computer-implemented method and system that utilize spatial descriptors to efficiently screen for potential collisions. This involves obtaining trajectory information, calculating spatial descriptors by mapping orbital paths onto a unit sphere, and performing set intersection comparisons to identify potential collision risks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional trajectory calculation and position comparison methods are used to identify collision risks, then measurement precision of collision risk is improved, but productivity of collision screening deteriorates due to very large computation requirements
Solution Approach 1:
The patent segments the collision screening process into two distinct phases: a broad phase using spatial descriptors (octrees, bounding volumes) to quickly eliminate non-colliding objects, and a narrow phase using precise trajectory calculations only for objects that pass the broad phase filter. This segmentation resolves the contradiction by enabling rapid initial screening while maintaining accurate collision detection for relevant objects.
Solution Approach 2:
The patent performs preliminary computation of spatial descriptors (such as octrees and bounding volumes) for all objects before the actual collision screening occurs. These pre-computed descriptors enable fast broad-phase filtering without requiring full trajectory calculations at screening time, thus improving productivity while preserving measurement precision in the subsequent narrow phase.
2Reliability
If trajectory calculations are performed for a large number of space objects to maintain comprehensive collision monitoring, then reliability of collision detection is improved, but loss of energy increases due to computational requirements
Solution Approach 1:
The patent extracts only the essential spatial information needed for collision detection into compact descriptors (such as octrees and bounding volumes), separating this from the full trajectory data. This extraction enables reliable collision monitoring for many objects while significantly reducing the computational energy required, as the descriptors are much smaller and faster to process than complete trajectory datasets.
Solution Approach 2:
The patent applies partial action by performing simplified broad-phase collision checks using spatial descriptors for all objects, and only performing the more computationally intensive narrow-phase trajectory calculations for a subset of objects that pass the broad phase filter. This approach maintains detection reliability for all objects while reducing energy consumption by avoiding excessive full-trajectory calculations for every object pair.
3Measurement precision
If high-resolution position predictions are calculated for near real-time collision screening, then measurement precision of position is improved, but difficulty of detecting and measuring increases due to computational complexity
Solution Approach 1:
The patent segments position prediction into two levels: coarse-position predictions using spatial descriptors for broad-phase filtering (low computational complexity), and fine-position predictions using full trajectory calculations only for objects passing the broad phase (high precision, but applied selectively). This segmentation resolves the contradiction by achieving high measurement precision where needed while keeping overall computational complexity manageable.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A method for orbital collision screening comprising, obtaining trajectory information of a plurality of objects moving on predictable paths. For each one of the plurality of objects, based upon respective trajectory information of the one of the plurality of objects, computing, a respective spatial descriptor of the path of the one of the plurality of objects, and storing the respective spatial descriptors of each of the plurality of objects in a data structure. Subsequently obtaining trajectory information of a further object, and based upon the trajectory information of the further object, computing a spatial descriptor of the path of the further object. Making first comparisons of the spatial descriptor of the further object against the respective spatial descriptors of each of the plurality of objects stored in the data structure to determine whether each of these first comparisons indicates a possible collision risk. Based upon each of the first comparisons, if the first comparison indicates a possible collision risk, determining a result of a close approach determination between the respective trajectory information of the respective one of the plurality of objects and the trajectory information of the further object, and taking an action based on result of the close approach determination satisfying a predetermined threshold.