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Record W2014682489 · doi:10.1109/icwits.2012.6417846

Cross polarization performance of high gain antennas in the presence of phase errors

2012· article· en· W2014682489 on OpenAlexaff
Z. Allahgholi Pour, L. Shafai

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSuperconducting and THz Device Technology
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsOpticsPolarization (electrochemistry)Monopulse radarOffset (computer science)RadomeDiagonalLinear polarizationPhysicsEngineeringComputer scienceMathematicsTelecommunicationsLaserGeometryAntenna (radio)Radar

Abstract

fetched live from OpenAlex

The effects of asymmetric linear phase errors on the cross polarization of offset reflector antennas were studied. Both single TE11 mode and matched dual-mode feeds were investigated. For the former single mode feed, it was shown that the phase error significantly deteriorated the cross polarization performance with the increased non-uniformity of the phase patterns, particularly at the diagonal plane. As for the primary matched feeds, the effect of asymmetric linear phase errors, applied only to the TE21 mode, on the cross polarization of offset reflector antennas was investigated. In practice, such phase errors are the result of separate phase centre locations of each TE11 and TE21 modes. A broad range of f/D ratios were studied. It was shown that the cross polarization levels drastically increased at both inter-cardinal and asymmetry planes. More interestingly, the cross polarization pattern had a broadside shape rather than a boresight-null. The results were the same as the radome effects on the cross polarization of monopulse tracking systems were reported.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.021
GPT teacher head0.295
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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