Adaptive gain optimization of a C-Band reflectarray with phase tunable elements
Bibliographic record
Abstract
Microstrip reflectarray antennas are currently considered for satellite missions requiring low cost, small stowage volume during launch and lightweight solutions. An essential characteristic of this kind of antenna is the possibility of having a steerable main beam due to the reflectarray's phase-tunable elements. The tunable units could be made of varactors diodes, as described in [1]. Following this work, a planar array prototype of 5x6 elements was used to demonstrate beam steering capability, but unexpected differences of 2 dB or more were noted between the measured and expected gains. It was conjectured that this loss could be attributed to non-optimal phase profiles imposed on the elements, possibly resulting from variability in the diodes, non-constant angle of incidence, fabrication errors, etc. The object of this paper is to implement an adaptive gain optimization and determine to what level the unexpected losses can be compensated by tuning all the scattering cells.
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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 | 0.000 |
| 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 | 0.001 | 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".