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Record W2060072310 · doi:10.1109/antem.2010.5552363

Design of a light–weight digital beam forming antenna for future sar applications

2010· article· en· W2060072310 on OpenAlexaff
Brian Cascarano, Jerome Colinas, Ralph Girard, Patrick Plourde

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Optimization
Canadian institutionsCanadian Space Agency
Fundersnot available
KeywordsSynthetic aperture radarPhased arrayAntenna (radio)Aperture (computer memory)Computer scienceRadarBeam (structure)X bandPhysicsElectrical engineeringTelecommunicationsEngineeringOpticsArtificial intelligenceAcoustics

Abstract

fetched live from OpenAlex

The CSA has been working actively during the past decade on developing various technologies for improving the capabilities of SAR antennas. Various techniques have been investigated for decreasing the mass per unit of area as well as improving the electronic capabilities of the radar. These efforts were combined to form a new concept that is presented here. The concept was defined for C-band applications but could also be applied at lower frequency. The radar antenna has a total area of 38 m2. The central aperture (~10 m2) is used on transmit and receive while the wings are receive only phased arrays spanning a total area of 28 m2. The central aperture transmits a large beam and the receive aperture captures the echo simultaneously from various directions through a digital beam synthesis.

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)0.000
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: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.003

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 head0.009
GPT teacher head0.204
Teacher spread0.195 · 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

Citations0
Published2010
Admission routes1
Has abstractyes

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