Control of Two-Dimensional Leaky-Wave Amplitude Tapering in PRS Antennas for Sidelobe Suppression
Bibliographic record
Abstract
Two-dimensional (2-D) partially reflective surface (PRS) antennas have attracted considerable interest over the past twenty years owing to their simple architecture and high‐gain capability. Despite extensive efforts to enhance gain and bandwidth, the sidelobe suppression—a critical requirement in many high‐directivity applications—has received comparatively little attention. In this work, we introduce a systematic design methodology for controlling the leaky‐wave amplitude distribution across a 2-D PRS aperture to meet specified beam‐ shaping objectives, with particular emphasis on sidelobe reduction. First, we derive an explicit relationship between the PRS reflection coefficient and the attenuation constant (leakage ratio), which enables direct calculation of the local leaky‐field amplitude on the aperture. Next, by enforcing energy conservation within the planar cavity formed by the PRS and a metallic ground plane, we develop a 2-D power‐transmission framework— presented in both continuous and discrete formulations—that relates local leakage power to the internal guided‐wave power distribution. This framework permits precise tailoring of the aperture amplitude profile and, consequently, the far-field radiation pattern. To validate the proposed approach, four PRS antennas incorporating phase‐correcting surfaces were designed, each exhibiting a prescribed amplitude taper. Measured and simulated results demonstrate excellent agreements and confirm predicted sidelobe suppression, thereby validating the efficacy of the method.
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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) | 0.001 | 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 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".