MétaCan
Menu
Back to cohort
Record W2267441744 · doi:10.4218/etrij.16.0115.0974

Accurate Characterization of T/R Modules with Consideration of Amplitude/Phase Cross Effect in AESA Antenna Unit

2016· article· en· W2267441744 on OpenAlexaff
Chang‐Soo Ahn, Sang-Mi Chon, Seon-Joo Kim, Young‐Sik Kim, Juseop Lee

Bibliographic record

VenueETRI Journal · 2016
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Optimization
Canadian institutionsNexen (Canada)
Fundersnot available
KeywordsAttenuator (electronics)Phase shift moduleAmplitudeElectronic engineeringEngineeringPhase (matter)Electrical engineeringPhysicsOpticsInsertion lossAttenuation

Abstract

fetched live from OpenAlex

In this paper, an accurate characterization of a fabricated X-band transmit/receive module is described with the process of generating control data to correct amplitude and phase deviations in an active electronically scanned array antenna unit. In the characterization, quantization errors (from both a digitally controlled attenuator and a phase shifter) are considered using not theoretical values (due to discrete sets of amplitude and phase states) but measured values (of which implementation errors are a part). By using the presented procedure for the characterization, each initial control bit of both the attenuator and the phase shifter is closest to the required value for each array element position. In addition, each compensated control bit for the parasitic cross effect between amplitude and phase control is decided using the same procedure. Reduction of the peak sidelobe level of an array antenna is presented as an example to validate the proposed procedure.

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)0.001
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
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.015
GPT teacher head0.263
Teacher spread0.248 · 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

Citations5
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueETRI JournalSame topicAntenna Design and OptimizationFrench-language works237,207