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Record W2483942882 · doi:10.1049/iet-rsn.2016.0320

Radar system with enhanced angular resolution based on a novel frequency scanning reflector antenna

2016· article· en· W2483942882 on OpenAlexaff
Francis Siaka, Mona Akbarniai Tehrani, Jean Jacques Laurin, Yvon Savaria

Bibliographic record

VenueIET Radar Sonar & Navigation · 2016
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Optimization
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsReflector (photography)Periscope antennaOpticsAntenna (radio)RadarResolution (logic)Remote sensingPhysicsAntenna measurementComputer scienceTelecommunicationsGeologyArtificial intelligence

Abstract

fetched live from OpenAlex

A radar system that uses a novel multi beam reflector antenna based on the frequency scanning principle is presented. The reflector primary source consists of a frequency multiplexer coupled to eight horn antennas radiating at different frequencies. A prototype of the system working in the X band is demonstrated. It is shown that over a frequency variation of only 2.2%, the main beam direction can be scanned over a sector of 50°. Frequency multiplexing allows an eight‐fold increase in scanning speed compared with purely mechanically rotated antennas. An experiment has been conducted to demonstrate the target detection capabilities of the radar. It is shown that by using a time‐multiplexed combined radiation pattern from mechanical and electrical scanning, it is possible to detect multiple targets beyond the antenna angular resolution limited by its beamwidth. Post processing of the received data from this composite scanning leads to the detection of two targets with angular separation equal to half the antenna beamwidth.

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: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.009
GPT teacher head0.205
Teacher spread0.196 · 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

Citations6
Published2016
Admission routes1
Has abstractyes

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