MUSIC-Enhanced CFARforHighFrequency Over-the-Horizon Radar
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".