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Record W2188399781

MUSIC-Enhanced CFARforHighFrequency Over-the-Horizon Radar

2007· article· en· W2188399781 on OpenAlex

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aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRadar Systems and Signal Processing
Canadian institutionsnot available
Fundersnot available
KeywordsBeamwidthAzimuthBeamformingComputer scienceRadarSynthetic aperture radarRemote sensingArtificial intelligenceGeologyTelecommunicationsOpticsPhysicsAntenna (radio)
DOInot available

Abstract

fetched live from OpenAlex

To increase thenumber oflocation options foran ofdegraded azimuth information andwedonotaddress the HF surface-wave radar(HFSWR)there issignificant interest issue ofreduced sensitivity. inreducing thephysical size ofthereceive array. Reducing the Inthispaper, we evaluate theeffect ofreducing the aperture results ina degradation ofbothsensitivity and physical aperture ofthelinear receive arrayusedinHF azimuth information. Azimuthaccuracy mayberetained by surface-wave radar(lIESWR) and usingpost-detection theuseofhigh-resolution methods(such asMUSIC)thathave asignificantly smaller beamwidth thanstandard beamforming.azimuthre-estimation by high-resolution methodsto Itisexpected thattheapplication ofthese high-resolution maintain azimuth resolution, accuracy, andhencetracking methods will helpretain azimuth information withreduced performance. Sincehigh-resolution methods(suchas aperture size. Thispaper evaluates theeffects ofreducing the MUSIC(1)) havemuchsmaller beamwidths thanstandard physical aperture ofthelinear receive arrayusedinHFSWR beamforming, itisexpected thattheapplication ofthese and usingpost-detection azimuthre-estimation by high- resolution methods tomaintain azimuth resolution, accuracy,methods will helpimprove tracking performance. However, andhencetracking performance. Thispaperislimited to sincethedetection itself continues tobe performed by evaluating theeffect ofincreased azimuth beamwidth anddoes standard beamforming andConstant FalseAlarmRate notaddress theissue ofreduced radar sensitivity. Dataforthe (CFAR)detection, thenon-linear behaviour ofpre-detection evaluation wasobtained fromanHFSWR systemlocated at high-resolution methods canbeavoided. Theseundesired CapeRace,Newfoundland, Canada.The accuracy ofthe detectionace,Ntr oidforuldland, .. ~~~~~~tracking performance iscompared tostandard CFAR Thereissignificant interest inreducing thephysical size of proceing using efl 1emearry t h shortened theecevearayof Hig Frqueny (F) adarwitout processing using thefull 16-element array. Theshortened thereceive array ofaHighFrequency (lIE) radar without compromisingoverallperformance. From an arraydataprocessed using theMUSIC-Enhanced CFAR implementation point ofview, smaller arrays result ina yields similar tracking tothefullaperture arraydata significant reduction intherequired physical extent ofthe processed using thestandard CFARprocessing. Thispaperisoutlined asfollows. A brief review ofthe radarnsite adtee inraehnubrflcio * * * 1 rr ~~~~the realistic setting ofafield experiment inSection V.The limttesopeof hisinvstiatin t evluaingtheeffctaccuracies ofthealgorithms arecompared, along withthe

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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 score0.568
Threshold uncertainty score0.380

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 head0.009
GPT teacher head0.212
Teacher spread0.203 · 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

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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