A Dual-Purpose Camera for Attitude Determination and Resident Space Object Detection on a Stratospheric Balloon
Bibliographic record
Abstract
Space systems play an integral role in every facet of our daily lives, including national security, communications, and resource management. Therefore, it is critical to protect our valuable assets in space and build resiliency in the space environment. In recent years, we have developed a novel approach to Space Situational Awareness (SSA), in the form of a low-resolution, Wide Field-of-View (WFOV) camera payload for attitude determination and Resident Space Object (RSO) detection. Detection is the first step in tracking, identification, and characterization of RSOs, including natural and artificial objects orbiting the Earth. A space-based dual-purpose camera that can provide attitude information alongside RSO detection can enhance the current SSA technologies which rely on ground infrastructure. A CubeSat form factor payload with real-time attitude determination and RSO detection algorithms was developed and flown onboard the CSA/CNES stratospheric balloon platform in August 2023. Sub-degree pointing information and multiple RSO detections were demonstrated during operation, with opportunities for improvement discussed. This paper outlines the hardware and software architecture, system design methodology, on-ground testing, and in-flight results of the dual-purpose camera payload.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".