Design of Linear Array-Fed Fabry-Perot Cavity Antennas for High Gain and Low Sidelobe Level
Bibliographic record
Abstract
The design of a linear Fabry-Perot (FP) cavity antenna fed with unequally spaced subarrays is presented. The FP cavity is characterized by its dominant leaky mode and the dispersion curves based on the finite element analysis of the eigenmode problem. The superposition of the excited leaky waves is used to model the array-fed FP cavity antenna. A hybrid optimization method incorporating convex$\ell_{1}$-norm minimization and particle swarm optimization is applied to the model to divide the source array into a minimum number of subarrays, while satisfying the radiation and source location constraints. The synthesis results yield a linear FP cavity antenna at 10 GHz with a half power beamwidth of 0.93°, aperture efficiency of 85.1%, and sidelobe level of -17.6 dB, achieved with only a single subarray.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".