Power Pattern Synthesis With Peripherally Excited Phased Arrays
Bibliographic record
Abstract
Peripherally excited (PEX) phased arrays have been demonstrated as an effective way to realize some aspects of phased array performance with a simple design and reduced cost. This work develops a method to realize shaped beams with PEX arrays by controlling the relative magnitude and phase of the antenna’s peripheral sources. Through a simple model of fields in a parallel-plate waveguide, a linear system of equations can be defined and solved to find the peripheral source excitations that best approximate a desired field pattern. This model is used to solve for a uniform broadside beam and yields a higher aperture illumination efficiency than a broadside beam obtained from an equal-amplitude excitation. A cosecant beam is also synthesized, showing good agreement with the goal beam pattern. The linear system of equations can be easily integrated into other beam synthesis techniques for increased design flexibility. A particle swarm optimization (PSO) is used to solve for controlled sidelobe levels, flat-top, and multibeam patterns. Beams realized with full-wave simulation show good agreement with the ideal and predicted beams.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".