Compact wideband twofold orthomode transducer
Bibliographic record
Abstract
Satellite networks now play an important role in various applications due to their unique features of global coverage and mobility assistance. Low Earth Orbit (LEO) satellites are currently gaining popularity in the wireless communications community, as they will be heavily used in future wireless communication networks. To enable polarization diversity, satellite systems commonly use dual-polarized antennas. Orthomode transducers (OMTs) are deployed in such systems to feed the antennas with the two orthogonal polarizations. The objective OMT is featured with deep matching levels, high isolation levels between its ports as well as a compact cross-sectional footprint. In this article, we propose a twofold OMT that is suitable for LEO satellite ground station applications. The proposed design covers a bandwidth ratio of about 54.6% with a deep matching level and high isolation. The electrical cross-sectional size of the proposed design is 4 λ o by 2.2 λ o , where λ o is calculated at the central frequency of operation. This promotes the proposed design for MIMO satellite applications. Moreover, the prototype for the design is fabricated and compared, where the measured responses are in good agreement with the simulated ones. Finally, the proposed structure is studied for compatibility with the LEO satellite feeding structures regarding thermal, power, and passive intermodulation analysis. This analysis is a typical mandatory analysis for space qualified units in the space industry.
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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 | 0.001 |
| Open science | 0.000 | 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".