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Millimeter-Wave Planar Antenna Array for Radar and Sensing Applications

2023· article· en· W4327927708 on OpenAlexaff
Yazan Al-Alem, Syed M. Sifat, Yahia M. M. Antar, Ahmed A. Kishk

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsConcordia UniversityRoyal Military College of CanadaRoyal Ottawa Mental Health CentreQueen's University
Fundersnot available
KeywordsAntenna measurementCoaxial antennaMicrostrip antennaAntenna arrayAntenna efficiencyDipole antennaRadiation patternAntenna factorPlanar arrayCollinear antenna arrayPatch antennaAntenna gainOpticsComputer scienceAntenna (radio)OptoelectronicsMaterials scienceTelecommunicationsPhysics

Abstract

fetched live from OpenAlex

We propose an efficient high gain millimeter-wave planar antenna array. The packaging of the antenna array feeding structure is eliminated by aggregating the feeding network in between the antenna elements, which has a significant advantage in maintaining neat and symmetric radiation characteristics with low cross polarization level. The proposed antenna array is extremely low in cost and can be used as either a linearly or circularly polarized antenna array. The antenna array has a realized gain of 20 dBi in both scenarios. The matching bandwidth is 4.1 % and the 3-dB axial ratio bandwidth is 6%. The antenna array only uses a single substrate layer with no need for any vias. To switch to circular polarization operation, a 3D printed dielectric polarizer is used. The proposed antenna array suits well various applications at 24 GHz, while maintaining high performance metrics, and extremely low cost. The antenna array can be easily integrated with transceivers due to the use of printed microstrip line technology.

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: Methods · Consensus signal: none
Teacher disagreement score0.968
Threshold uncertainty score0.274

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 communication0.0000.000
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 head0.024
GPT teacher head0.221
Teacher spread0.197 · 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
GenreMethods

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 routes1
Has abstractyes

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