MétaCan
Menu
Back to cohort
Record W4406857725 · doi:10.1109/trs.2025.3534521

Space-Domain Awareness Using Over-the-Horizon Radar

2025· article· en· W4406857725 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

VenueIEEE Transactions on Radar Systems · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvanced SAR Imaging Techniques
Canadian institutionsRoyal Military College of CanadaDefence Research and Development Canada
Fundersnot available
KeywordsOver-the-horizon radarRadarHorizonComputer scienceSpace (punctuation)Remote sensingGeographyMathematicsTelecommunicationsGeometry

Abstract

fetched live from OpenAlex

The use of existing over-the-horizon radar (OTHR) systems as space-domain awareness (SDA) sensors is experimentally evaluated by tracking several International Space Station (ISS) passes under different solar activity conditions. Using range and Doppler measurements, a single-frequency ionospheric correction technique is introduced and is shown to be critical to the implementation of accurate SDA using OTHR. This single-frequency technique is also useful for monitoring the ionosphere total electron content (TEC) using a space target without very accurate prior knowledge of its orbital parameters. All measurements and orbit determination results are validated with truth data provided by the National Aeronautics and Space Administration (NASA). Although it is determined that angle-of-arrival (AOA) measurements are not accurate enough for accurate SDA, orbit determination using single-pass observations from a single site are shown to yield position and velocity errors that can be better than 500 m and 0.7 m/s with a radar bandwidth of only 10 kHz. Accurate SDA using OTHR is determined to be possible especially at night or in periods of solar minimum.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.966
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.265
Teacher spread0.252 · 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