A Simplified Feed Model for Investigating the Cross Polarization Reduction in Circular- and Elliptical-Rim Offset Reflector Antennas
Bibliographic record
Abstract
An analytic model for the primary feed of offset reflector antennas is presented that facilitates a more general investigation of the cross polarization reduction in both asymmetric and inter-cardinal planes. It includes both first and second order azimuthal modes, primarily the TE11and TE21type modes, and allows selection of symmetric and asymmetrical patterns, with different field tapers in the principal planes. Using this model first the influence of the second order TE21mode on the cross polarization of an offset reflector with a circular rim is investigated. Then, the problem for an offset reflector with an elliptic rim is also studied. It is shown that minimizing the cross polarization in the asymmetric plane does not necessarily reduce it globally, as in the inter-cardinal plane it remains high. The procedure for reduction of the cross polarization globally and its effects on the sidelobe levels of the reflector antenna are also investigated. With the proposed feed model, the aperture efficiency of the reflector antenna is improved compared with a standard Gaussian feed with the same edge taper. Based on this study, a dual-mode circular waveguide horn is also proposed and designed. Its performance on an offset reflector antenna is studied and shown that the cross polarization levels are reduced quite satisfactorily within a respectable frequency band.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".