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Record W1986587640 · doi:10.1109/tgrs.2012.2184798

Detection and Estimation With RADARSAT-2 Moving-Object Detection Experiment Modes

2012· article· en· W1986587640 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.

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

VenueIEEE Transactions on Geoscience and Remote Sensing · 2012
Typearticle
Languageen
FieldEngineering
TopicAdvanced SAR Imaging Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMoving target indicationSynthetic aperture radarComputer scienceObject detectionRemote sensingComputer visionInverse synthetic aperture radarPhase centerArtificial intelligencePosition (finance)Antenna (radio)Radar imagingRadarReal-time computingContinuous-wave radarTelecommunicationsGeologyPattern recognition (psychology)

Abstract

fetched live from OpenAlex

This paper describes in detail several multichannel variants of the famous displaced phase center antenna (DPCA) method suitable for spaceborne multichannel synthetic aperture radar ground moving target indication (GMTI), which has become available through the RADARSAT-2 moving-object detection experiment (MODEX). A flexible signal processing architecture was developed at Defense Research and Development Canada to support R&D work in GMTI and to provide a tool for MODEX system validation. The presented multichannel DPCA method is one of the first algorithms that have been implemented and successfully tested using this architecture. The main objective is to provides a simple, yet effective and robust way to detect ground moving vehicles and to estimate their position and velocity. This work forms a baseline for further advancement in the GMTI area.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.797
Threshold uncertainty score0.532

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 communication0.0000.001
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 head0.010
GPT teacher head0.234
Teacher spread0.224 · 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