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Record W2104337872 · doi:10.1049/ip-rsn:20045094

Ground moving target parameter estimation for two-channel SAR

2006· article· en· W2104337872 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

VenueIEE Proceedings - Radar Sonar and Navigation · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced SAR Imaging Techniques
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsSynthetic aperture radarAzimuthComputer scienceChannel (broadcasting)Remote sensingFilter (signal processing)Track (disk drive)Inverse synthetic aperture radarInterferometryRadarGeologyRadar imagingComputer visionTelecommunicationsPhysicsOptics

Abstract

fetched live from OpenAlex

The author introduces and analyses the performance of different techniques to estimate the parameters of ground moving targets in multi-channel synthetic aperture radar (SAR) data. Candidates are matched filter banks, the along-track interferometric phase and direction-of-arrival estimation methods, which can work in either the raw data or in the compressed SAR image domain. Of particular interest are systems with only two channels because many existing or near-future SAR systems, such as RADARSAT-2 and TerraSAR-X, are restricted to a maximum of two sub-apertures. Desired parameters are the two velocity components (along- and across-track), acceleration if present and the true azimuth location. Theoretical results are evaluated and illustrated with experimental airborne SAR data.

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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.559
Threshold uncertainty score0.772

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 head0.008
GPT teacher head0.242
Teacher spread0.234 · 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