Space Debris Detection Using Orbit Propagation Models
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Solution Overview
Problem
Current methods for detecting space debris in geocentric orbits using image processing are inefficient due to the need for trial and error in determining the motion vector of debris, requiring extensive processing time, especially when dealing with low-brightness debris that is difficult to distinguish from the background.
Innovation Solution
A method that employs a debris breakup model and orbit propagation model to estimate the motion vector of space debris, reducing the search region and processing time by generating virtual debris pieces and calculating their orbits, allowing for efficient detection using a stacking method.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the stacking method is applied to detect space debris by shifting and stacking cut-out images, then the detection capability is improved, but the processing time increases dramatically due to trial and error required to determine motion vectors
Solution Approach 1:
The patent applies preliminary action by using orbit propagation models to predict the future positions of space debris before actual detection. The system calculates expected trajectories based on current orbital parameters, allowing the stacking method to be applied directly without extensive trial and error for motion vector determination. This preliminary calculation of debris positions enables efficient image processing by providing advance knowledge of where debris should appear in subsequent images.
2Measurement precision
If trial and error is used to determine motion vectors for stacking images, then the detection accuracy is improved, but the processing time increases to months or years
Solution Approach 1:
The patent replaces the mechanical trial-and-error search process with a theoretical model-based approach. Instead of systematically testing various motion vectors (mechanical search), the system uses orbit propagation models to calculate the expected motion trajectories of space debris based on gravitational physics and orbital mechanics. This substitution of physical modeling for computational search dramatically reduces processing time from months to practical levels while maintaining detection accuracy.
3Ease of operation
If general-purpose computers are used for image processing, then accessibility is improved, but the processing time becomes excessively long for effective detection
Solution Approach 1:
The system performs preliminary orbit propagation calculations to determine expected debris positions and motion vectors before executing the image stacking process. By pre-calculating where debris should appear based on orbital mechanics, the system eliminates the need for lengthy trial-and-error searches during the actual image processing, enabling general-purpose computers to complete analysis within practical timeframes.
4Adaptability or versatility
If low-brightness debris is detected using conventional methods, then detection coverage is improved, but the processing time increases due to difficulty in distinguishing from background
Solution Approach 1:
The patent replaces mechanical image processing search with theoretical orbit propagation models that predict the precise positions and motion characteristics of space debris. By calculating expected trajectories based on gravitational physics, the system can identify low-brightness debris through their predicted motion patterns rather than relying solely on brightness thresholds, enabling detection of faint objects without excessive processing time.
Data Source
AI summary
A method of detecting space debris includes: generating a virtual space debris in accordance with the law of conservation of mass by applying a debris breakup model to an object of breakup origin; calculating an orbit of each virtual space debris based on a debris orbit propagation model; and generating appearance frequency distribution of a motion vector of each virtual space debris on the celestial sphere based on the orbit calculation. The above operations are executed multiple times. The method further includes setting a search range vector based on a motion vector having a high level of the appearance frequency distribution of the motion vector, and applying a stacking method to regions in images captured at time intervals during the fixed point observation, the regions being shifted along the search range vector sequentially in the order of capture, thereby detecting space debris appearing on the images.