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Record W2980247784 · doi:10.1029/2019rs006868

Investigation of a 256‐Monopole Transmit Antenna Array for Over‐the‐Horizon Radar in Canada

2019· article· en· W2980247784 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueRadio Science · 2019
Typearticle
Languageen
FieldEngineering
TopicRadar Systems and Signal Processing
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsClutterRadarOver-the-horizon radarAzimuthComputer scienceCalibrationRemote sensingDoppler effectAntenna arrayAntenna (radio)AcousticsGeologyPhysicsTelecommunicationsOptics

Abstract

fetched live from OpenAlex

Abstract A 256‐monopole planar array is investigated as a potential transmit antenna covering the entire 3‐ to 18‐MHz band in an over‐the‐horizon radar (OTHR) operating at high latitudes in Canada. This array is relatively inexpensive, simple to build, and offers the azimuth and elevation resolutions necessary to defeat the auroral clutter which has traditionally limited the operation of OTHR at high latitudes. It is demonstrated that excellent clutter rejection ratios are possible with this antenna array and accurate calibration, but significant performance degradation occurs with calibration errors in particular in the lower portion of the operating frequency band. Various calibration approaches and error mechanisms are studied. A new approach combining multiple‐input‐multiple‐output (MIMO) radar techniques at lower frequencies and conventional transmit null steering at higher frequencies is proposed and evaluated. This approach enhances the robustness of the array to calibration errors while preserving the radar unambiguous range‐Doppler space across the operating frequency band.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.380
Threshold uncertainty score0.916

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.008
GPT teacher head0.186
Teacher spread0.178 · 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