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Record W2088526918 · doi:10.1109/radar.2002.1174654

Ship detection and tracking using HF surface wave radar

2003· article· en· W2088526918 on OpenAlexaffabout
Hank Leong, Chris Helleur, María Teresa de Tena Rey

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRadar Systems and Signal Processing
Canadian institutionsDefence Research and Development Canada
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsRadarNavyTracking (education)Radar trackerRadar detectionSea trialRemote sensingGeologyTelecommunicationsComputer scienceMarine engineeringGeographyEngineeringOceanographyArchaeology

Abstract

fetched live from OpenAlex

The Canadian Department of National Defence (DND) conducted a joint trial involving multiple sensors in the detection and tracking of ships in the Grand Banks of Canada in March 2000, including the HF surface wave radar (HFSWR) system at Cape Race, Newfoundland. One objective of the trial was to evaluate the detection and tracking capabilities of the HFSWR system. Three co-operative ships were used: a Canadian Navy patrol frigate named Ville de Quebec and two small fishing vessels named Anne S. Pierce and Arctic Pride. We present some results of the detection and tracking of these co-operative ships using the HFSWR. The radar had difficulties tracking ships near Bragg lines, i.e., the first-order sea echoes of the radar. A revised algorithm is also presented to detect ships near Bragg lines.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.190

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.215
Teacher spread0.184 · 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

Citations3
Published2003
Admission routes2
Has abstractyes

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