Mitigation of Misalignment Errors Over Inter-Satellite FSO Energy Harvesting : (Invited Paper)
Bibliographic record
Abstract
In this paper, the impact of the acquisition, tracking, and pointing (ATP) module utilization on inter-satellite energy harvesting is investigated for 1U (0.1 × 0.1 × 0.1 m) and 12U (0.2 × 0.2 × 0.3 m) satellites for adaptive beam divergence and the corresponding distances while maintaining the spot diameters. Random elevation and azimuth misalignment error angles at both the transmitter and the receiver are modeled with Gaussian distribution hence the radial pointing error angle is modeled with Rayleigh distribution. The Monte Carlo approach is used to determine mean radial error angles for both transmitter and receiver in the non-ATP and ATP cases. The average harvested powers are analyzed as a function of the transmit powers and inter-satellite distances for both 1U and 12U satellites while considering the minimum power requirements. Our simulation results show that in the non-ATP case, the minimum required average harvested power cannot be achieved beyond 680 and 1360 km distances for 1U and 12U satellites, respectively, with a maximum transmit power of 1 kW. However, 2 W of average harvested power can be achieved at around 750 and 1500 km for 1U and 12U satellites, respectively, with a transmit power of 27 W in the presence of an ATP mechanism.
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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 | 0.000 | 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) | 0.001 | 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 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".