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Record W2206422526

Optimum GMTI Processing for Space-based SAR/GMTI Systems - Simulation Results

2010· article· en· W2206422526 on OpenAlexaff
Delphine Cerutti‐Maori, Ishuwa Sikaneta

Bibliographic record

VenueSynthetic Aperture Radar (EUSAR), 2010 8th European Conference on · 2010
Typearticle
Languageen
FieldEngineering
TopicAdvanced SAR Imaging Techniques
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsMoving target indicationComputer scienceSynthetic aperture radarPhase centerComputer visionArtificial intelligenceRemote sensingAntenna (radio)RadarRadar imagingGeographyTelecommunicationsContinuous-wave radar
DOInot available

Abstract

fetched live from OpenAlex

In Cerutti-Maori, Sikaneta, Optimum GMTI Processing for Space-based SAR/GMTI Systems - Theoretical Derivation, the processing methods, EDPCA (Extended Displaced Phase Center Antenna) and ISTAP (Imaging Space Time Adaptive Processing), were proposed for optimum GMTI (Ground Moving Target Indication). This paper tests these methods using simulated data and contrasts the properties of each method. This paper also comments on the GMTI performance of current generation satellites because the simulated data are based upon proposed RADARSAT-2 modes.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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 integrity0.0010.000
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 head0.026
GPT teacher head0.262
Teacher spread0.237 · 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 designSimulation or modeling
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

Citations13
Published2010
Admission routes1
Has abstractyes

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