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Record W2200486666

Innovative Capabilities of the RADARSAT Constellation Mission

2010· article· en· W2200486666 on OpenAlexaboutno aff
Alan Thompson

Bibliographic record

VenueSynthetic Aperture Radar (EUSAR), 2010 8th European Conference on · 2010
Typearticle
Languageen
FieldEngineering
TopicSynthetic Aperture Radar (SAR) Applications and Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsConstellationRemote sensingPolarimetryComputer scienceSatelliteAzimuthSpacecraftSatellite constellationGround segmentSynthetic aperture radarSystems engineeringEnvironmental scienceAerospace engineeringGeologyEngineeringPhysicsOptics
DOInot available

Abstract

fetched live from OpenAlex

The RADARSAT Constellation Mission (RCM) is a Canadian SAR mission consisting of three C-band SAR satellites. RCM is currently being designed by a Canadian industrial team led by MacDonald-Dettwiler and Associates (MDA) under contract to the Canadian Space Agency. The emphasis of this paper is on providing a description of those capabilities of RCM that are unique or innovative. These unique or innovative capabilities include a constellation optimized for coherent change detection (CCD), a compact polarimetry mode, special imaging modes optimized for ship detection, and capabilities to support ocean current and ocean wind estimation. To support CCD, the system design includes maintaining the satellites in a narrow orbital tube, a tight requirement on azimuth antenna pointing control, and ScanSAR burst timing calculated from on-orbit spacecraft location data. For compact polarimetry, a capability to transmit circular polarization and receive H and V simultaneously is part of the design. For ship detection, innovative ScanSAR modes are used with a large number of beams and variable resolution and looks designed to optimize ship detection across a wide swath. In order to support ocean current and ocean wind estimation, a Doppler grid is included in the product meta-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.

How this classification was reachedexpand

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.855
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.218
Teacher spread0.205 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations15
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueSynthetic Aperture Radar (EUSAR), 2010 8th European Conference onSame topicSynthetic Aperture Radar (SAR) Applications and TechniquesFrench-language works237,207