Sunlit Orbital Debris Search with Hierarchical Track Processing
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Solution Overview
Problem
Existing systems struggle to efficiently detect sunlit orbital debris due to high sky background noise during twilight, especially for small debris, and require computationally intensive algorithms that are difficult to execute in real-time.
Innovation Solution
A system utilizing a ground-based telescope with a detector array and a hierarchical processing algorithm on graphics processors to compute tracks from detector data, building longer tracks from shorter ones, and converting them into debris brightness and orbital trajectory.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of moving object
If the detection system operates when the sun is near the horizon to maximize detection window, then the available time for debris detection is maximized, but the sky background noise increases making detection more difficult
Solution Approach 1:
The detection algorithm segments the 3D detector data into multiple 2D planes and processes each plane independently to identify linear tracks. This segmentation approach allows the system to handle the increased background noise by focusing computational effort on identifying coherent linear patterns rather than processing the entire noisy dataset as a single unit.
Solution Approach 2:
The patent transforms the debris detection problem from a 2D image analysis problem into a 3D volumetric data analysis problem by incorporating the time dimension. Debris tracks appear as linear features extending through multiple time frames, creating a distinctive 3D signature that can be differentiated from random background noise, thereby improving detection capability despite elevated sky background levels.
2Measurement precision
If computationally intensive algorithms are used to reject sky background noise, then detection accuracy improves, but processing time increases making real-time operation difficult
Solution Approach 1:
The algorithm divides the computationally intensive track detection task into smaller sub-tasks by processing data in manageable 2D planes and using hierarchical processing. This segmentation reduces the computational burden on any single processing unit while maintaining overall detection accuracy, enabling real-time operation.
Solution Approach 2:
The system performs preliminary processing of the detector data by organizing it into a 3D volume and pre-identifying potential track candidates before applying the full detection algorithm. This preliminary organization reduces the search space and computational requirements for the subsequent detection steps, enabling real-time processing.
3Measurement precision
If high frame rate cameras are used to isolate debris to few pixels per frame, then background rejection improves, but hardware complexity and cost increase
Solution Approach 1:
The patent replaces the need for extremely high frame rate hardware with a computationally intensive but algorithmically efficient approach. By using moderate frame rate cameras combined with hierarchical processing and linear track detection algorithms, the system achieves the same debris isolation precision without requiring prohibitively expensive high-speed camera hardware.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables real-time detection of sunlit orbital debris with high accuracy and low false alarms, allowing for immediate tracking and potential deflection.
Implementation Method 1
detects images of the sunlit debris crossing the field of the detector
Data Source
AI summary
The present disclosure provides a system that searches for and finds orbital debris that can be a hazard to satellites and the like, for which the debris is sunlit. The system includes a ground-based telescope pointed at the sky; a detector array that detects images of the sunlit debris crossing the field of the detector; and a processing system that computes tracks from the detector data using a hierarchical algorithm, which builds longer tracks from previously computed shorter tracks, determines whether the computed tracks correspond to valid debris detections, and converts the track computations into debris brightness and debris orbital trajectory.