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Record W2118426575 · doi:10.23919/eumc.2009.5295987

Multi-antenna system based on substrate integrated waveguide for Ka-band traffic-monitoring radar applications

2009· article· en· W2118426575 on OpenAlexaff
Xiaoping Chen, Lin Li, Ke Wu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsReturn lossAzimuthKa bandSlotted waveguideBandwidth (computing)RadarAntenna (radio)Ground planeOpticsAcousticsDipole antennaPhysicsComputer scienceSlot antennaTelecommunications

Abstract

fetched live from OpenAlex

In this paper, a multi-antenna system designed with one antenna for transmitter and the other three for receiver is proposed and demonstrated for Ka-band traffic-monitoring radar applications with simultaneous functionality of range, velocity and angle detection. Each antenna consists of 4×20 substrate integrated waveguide (SIW) slot array for wide azimuth field of view and low ground reflection. The scan angle of +5/−5 degree in azimuth plane (E-plane) for two receiver antennas, respectively, is simply realized by rotating the compact feeding network with a specific angle. The design details are given and the isolation between antennas with different orientations is also investigated. The prototyped antenna has a measured gain of about 22 dBi and side lobe suppression of 20 dB in the H-plane, while the bandwidth for the 10-dB return loss is 1.25 GHz.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.004

Distilled classifier scores by category (both heads)

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.016
GPT teacher head0.230
Teacher spread0.214 · 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

Citations11
Published2009
Admission routes1
Has abstractyes

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