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Record W2124447720 · doi:10.1109/radar.2003.1278823

Non-stationary interference cancellation in HF surface wave radar

2004· article· en· W2124447720 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRadar Systems and Signal Processing
Canadian institutionsMcMaster University
Fundersnot available
KeywordsClutterOver-the-horizon radarRadarInterference (communication)Computer scienceRadar horizonSurface waveVisibilityDoppler radarAntenna (radio)AcousticsContinuous-wave radarGeologyRadar imagingRemote sensingTelecommunicationsPhysicsOptics

Abstract

fetched live from OpenAlex

High frequency (HF) interference in surface wave over-the-horizon (OTH) radars typically exhibits a time-varying or non-stationary spatial structure. Adaptive beamformers that update the spatial filtering weight vector within the coherent processing interval (CPI) are likely to suppress such interference most effectively, but the intra-CPI antenna pattern fluctuations result in temporal de-correlation of the clutter which severely degrades sub-clutter visibility after Doppler processing. A robust adaptive beamformer that effectively suppresses non-stationary interference without degrading sub-clutter visibility is proposed. The new algorithm is computationally efficient and suitable for practical implementation. Its operational performance is evaluated using experimental data recorded by the Iluka HF surface wave (HFSW) OTH radar, located near Darwin in far north Australia.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.150
Threshold uncertainty score0.263

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 head0.012
GPT teacher head0.206
Teacher spread0.194 · 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

Citations17
Published2004
Admission routes1
Has abstractyes

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