Satellite Constellation Imaging for Accurate RSO Tracking
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Solution Overview
Problem
The increasing number of satellites in orbit around Earth poses a risk of collisions due to space debris, necessitating effective detection, identification, and mapping of resident space objects (RSOs) to mitigate collision risks and ensure safe space operations.
Innovation Solution
A system and method utilizing a constellation of low-cost space-based optical sensor payloads on multiple satellites in various orbital planes to capture celestial images, including RSOs and other celestial bodies, employing defocused imaging to enhance positional accuracy and generate celestial image features, which are processed using big data analytics and machine learning to identify and track RSOs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the number of satellites in orbit is increased to enhance imaging coverage and detection capability, then the ability to detect and map RSOs is improved, but the risk of collisions with space debris increases
Solution Approach 1:
The system divides the imaging task across multiple satellites in different orbital planes, with each satellite capturing a specific portion of the sky. This segmentation allows comprehensive RSO detection without requiring a single large satellite system, thereby reducing individual satellite size and collision risk while maintaining overall detection capability.
Solution Approach 2:
The patent transitions from two-dimensional Earth-based observation to three-dimensional space-based imaging by deploying satellites in multiple orbital planes. This dimensional expansion enables comprehensive sky coverage and improved RSO detection while distributing collision risk across multiple independent satellite platforms.
2Measurement precision
If defocusing is applied to the imaging optical arrangement to increase positional detection accuracy, then the ability to detect celestial image features is improved, but the image sharpness deteriorates
Solution Approach 1:
The system intentionally changes the focal parameter of the imaging optical arrangement from focused to defocused state. This parameter change spreads celestial image features over multiple pixels, increasing positional detection accuracy through improved signal-to-noise ratio while accepting reduced image sharpness as a trade-off for enhanced detection capability.
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 accurate mapping and tracking of RSOs, predicting potential collisions, and reducing the risk of debris-related satellite damage by generating detailed celestial image features and updating RSO databases for safer space operations.
Implementation Method 1
a plurality of sensors configured to define a plurality of pixels to detect light through the at least one imaging optical arrangement
Data Source
AI summary
A system includes a plurality of satellites in orbit around a celestial body in a plurality of orbital planes. Each satellite includes an imaging device having a field of view (FOV) to capture an image of a sky that includes celestial image features of resident space object (RSO), stars, and/or planets. The satellite processor is configured to receive image data from sensors in the imaging device, to increase a positional detection accuracy of the celestial image features by defocusing imaging optics of the imaging device, to capture image data in a volume of the sky as the FOV of the imaging device on each satellite moves in an orbital plane, and generate by a centralized computer at least 1,000 celestial image features using the image data transmitted from each of the satellites.