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Record W4313889918 · doi:10.3390/s23020731

Wideband Dual-Polarized Octagonal Cavity-Backed Antenna with Low Cross-Polarization and High Aperture Efficiency

2023· article· en· W4313889918 on OpenAlexafffund
Yanxia Liu, Dustin Isleifson, L. Shafai

Bibliographic record

VenueSensors · 2023
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaCMC Microsystems
KeywordsOpticsWidebandAntenna measurementAntenna factorComputer scienceAcousticsElectronic engineeringEngineeringAntenna (radio)PhysicsElectrical engineering

Abstract

fetched live from OpenAlex

Simultaneously enhancing multiple antenna performance parameters is a demanding task, especially with a challenging set of design goals. In this paper, by carefully deriving a compatible set of enhancement techniques, we propose a compact/lightweight/low-cost high-performance L-band octagonal cavity-backed hybrid antenna with multiple attractive features: dual-polarization, wide impedance bandwidth, low cross-polarization, high gain, and high aperture efficiency. The ground cavity is octagonal, which allows the antenna to have a small footprint, and, more importantly, low cross-polarization and high aperture efficiencies when compared to a commonly-used square design. The hybrid design relies on the resonance merging of two radiating elements, i.e., radiating feedlines and a conductive open prism, to form a wide impedance bandwidth. To permit polarization diversity and low cross-polarization, it is differentially and orthogonally fed. Herein, a series of parametric simulation studies on antenna configurations provide information on how to improve the impedance bandwidth and cross-polarization performance. To verify the simulation studies, an antenna prototype was fabricated and tested. Excellent agreement between the simulated and measured results was reached.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.966
Threshold uncertainty score0.703

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.006
GPT teacher head0.206
Teacher spread0.200 · 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 teacher head, 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

Citations4
Published2023
Admission routes2
Has abstractyes

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