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Record W4403277527 · doi:10.1109/ojap.2024.3477318

Beam Shaping of a Dual-Reflector Antenna Using a Reflectarray as Subreflector and Embedded Unit Cell Patterns

2024· article· en· W4403277527 on OpenAlexafffund
Marzieh Mehri Dehnavi, Jean‐Jacques Laurin

Bibliographic record

VenueIEEE Open Journal of Antennas and Propagation · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsReflector (photography)Periscope antennaDual (grammatical number)OpticsAntenna (radio)Beam (structure)Unit (ring theory)Fan-beam antennaCassegrain antennaMaterials sciencePhysicsAntenna measurementComputer scienceTelecommunicationsMathematicsLight source

Abstract

fetched live from OpenAlex

This work proposes a phase-only synthesis technique for shaping the beam of a circularly polarized dual-reflector antenna with a subreflector consisting of a reflectarray and a main parabolic reflector. The proposed technique exploits the element patterns of each reflectarray unit cell embedded in the whole system, including a feed horn, a reflectarray, and a main reflector. By using a penalty function that forces only the fitting of the desired and obtained patterns, the algorithm leads to a quasi-random phase distribution on the reflectarray and a poor radiation pattern. A term for minimizing the Laplacian of the phase distribution is added to the penalty function to force a smoothly varying phase distribution on the reflectarray. This modification provides more stable results and yields patterns with desired shapes and regular contours. The beam shaping capability of the algorithm is demonstrated with simulations of a 100-element reconfigurable circularly polarized reflectarray, by controlling independently the 10 dB beamwidth of the antenna in two orthogonal planes The algorithm is also validated experimentally. Beamwidth accuracies vary from 0 to 2.15 degrees.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.638

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.056
GPT teacher head0.321
Teacher spread0.265 · 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

Citations3
Published2024
Admission routes2
Has abstractyes

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