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Record W2257226590 · doi:10.1049/iet-rsn.2015.0196

Experimental validation of coherent multiple‐input multiple‐output radar antenna patterns

2015· article· en· W2257226590 on OpenAlexaff
Peter W. Moo, Pascale Sévigny, Tony Laneve

Bibliographic record

VenueIET Radar Sonar & Navigation · 2015
Typearticle
Languageen
FieldEngineering
TopicRadar Systems and Signal Processing
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsPhased arrayMIMORadiation patternAntenna (radio)Antenna arrayRadarElectronic engineering3G MIMOComputer scienceActive electronically scanned arrayOpticsPhysicsTelecommunicationsAcousticsRadar engineering detailsRadar imagingEngineeringBeamforming

Abstract

fetched live from OpenAlex

This study specifies the antenna radiation patterns of a linear array radar operating in a phased array configuration and in two colocated multiple‐input multiple‐output (MIMO) configurations. The MIMO‐1 configuration uses orthogonal transmission on all elements, while the MIMO‐2 configuration uses orthogonal transmission on the two end elements. The theoretical two‐way antenna radiation patterns are derived for all three configurations. Field experiments with an eight‐element, X ‐band linear array radar and trihedral targets are then described. The experimental mainbeam patterns are shown to match those of the theoretical patterns. MIMO‐1 is shown to have the same two‐way radiation pattern as that of the phased array radar configuration. Compared with MIMO‐1 and phased array, MIMO‐2 has enhanced angle estimation accuracy, lower gain, and higher sidelobes while only requiring two orthogonal waveforms on transmit.

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)0.002
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.029
GPT teacher head0.247
Teacher spread0.218 · 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

Citations2
Published2015
Admission routes1
Has abstractyes

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