Acquisition and Tracking Strategies for Satellite to Ground Optical Communication Systems
Why this work is in the frame
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Bibliographic record
Abstract
Optical wireless communication (OWC) offers a promising alternative to radio frequency (RF) based communication because it can support the increased demand for bandwidth in modern networks. This thesis examined three strategies that could be implemented to improve or simplify the design of a ground and satellite optical communication link. The acquisition of a laser beam emitted from a space orbiting satellite was examined. Atmospheric conditions and how they affect beam refraction was modeled using beam geometry and the refractive properties of air. Simulation results indicate that a beam with a large zenith angle is refracted to a higher degree than a beam with a smaller zenith angle. Beam refraction of an emitted beam with zenith angles of 61º and 82º reached the Earth surface with a peak power of 1179 photons/bit and 305 photons/bit respectively. Initial orbit estimation methods were examined, and it was found that Gauss’ Angles Only method was able to predict the azimuth and elevation of a target satellite with an average error of 6.38e−1. Which were positive results, and indicated that the Gauss method would be useful for initial orbit determination of an emitting satellite. Finally, a Extended Kalman Filter (EKF) state estimator was designed to evaluate whether the use of a Kalman filter is suitable for orbit determination when only using the angular observations that are available at an optical groundstation. Results indicated that when measurement errors of ±0.3 degrees were introduced into the system, position error state estimates reached a maximum of 6.9 km and 0.013 km/s. When the EKF was given smaller measurement errors of ±0.1 degrees, the errors in the state estimates were found to be a maximum of 1.4 km and 0.002 km/s. The results from the simulation for the state estimator indicated that an EKF can be applied to track the motion of a target satellite
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it