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Record W1841089197 · doi:10.1109/aps.2001.959686

Sidelobe apodization for high resolution of scattering centres in ISAR images

2002· article· en· W1841089197 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
TopicAdvanced SAR Imaging Techniques
Canadian institutionsDepartment of National DefenceUniversity of WinnipegUniversity of Manitoba
Fundersnot available
KeywordsApodizationInverse synthetic aperture radarSynthetic aperture radarComputer scienceRadar imagingScatteringOpticsImage formationFourier transformArtificial intelligenceRadarComputer visionResolution (logic)Image (mathematics)PhysicsTelecommunications

Abstract

fetched live from OpenAlex

Inverse synthetic aperture radar (ISAR) image processing is useful in identifying and isolating dominant scattering centres of a target for subsequent placement of radar absorbing material (RAM). ISAR image construction artifacts have the potential of obscuring low intensity scatterers in the image as well as blurring regions where closely separated scatterers occur. Spatially variant sidelobe apodization (SVA) is a technique that reduces sidelobe levels in a Fourier image while maintaining the image resolution that would be obtained using the rectangular window. We investigate the application of 2 versions of SVA to the ISAR image of a ship; these are the standard cosine-on-pedestal SVA and the new Kaiser window version of SVA. It is found that either SVA approach is able to find and isolate scattering centres. We also found that when polar reformatting is required, neither SVA version is a substitute for it, but applying SVA after polar reformatting gives excellent results.

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: Methods · Consensus signal: none
Teacher disagreement score0.828
Threshold uncertainty score0.296

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 head0.013
GPT teacher head0.230
Teacher spread0.217 · 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

Citations3
Published2002
Admission routes1
Has abstractyes

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