MétaCan
Menu
Back to cohort

Design of Series- fed Patch Array with Modified Binomial Coefficients for MIMO Radar Application

2021· article· en· W4213036580 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venue2021 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (APS/URSI) · 2021
Typearticle
Languageen
FieldEngineering
TopicRadar Systems and Signal Processing
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsSide lobeAzimuthMIMORadarTransmitterAcousticsComputer scienceElectronic engineeringAntenna (radio)TelecommunicationsPhysicsEngineeringOpticsChannel (broadcasting)

Abstract

fetched live from OpenAlex

In this paper, we propose a collocated antenna configuration having three transmitter and five receiver arrays for automotive MIMO Radar application. The individual antenna arrays consist of a seven-element series fed array with the feed provided at the edge. We introduce a modified-binomial coefficient-based excitation scheme to achieve improved side-lobe level (SLL) in series-fed patch arrays with edge feeding. The proposed MIMO configuration exhibits low SLL less than 16 dB and a wide field-of-view (FoV) of about 80° in the azimuth plane, along with satisfactory angular resolution (5.82°) and low cross-polar level (30 dB), rendering it extremely suitable for automotive medium-range radar (MRR) application.

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.

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)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.584
Threshold uncertainty score0.798

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.014
GPT teacher head0.235
Teacher spread0.221 · 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