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Record W4411019455 · doi:10.1109/lgrs.2025.3576665

Modeling the Impact of Sporadic-E on Over-the-Horizon Radar (OTHR) in the Polar Region

2025· article· en· W4411019455 on OpenAlexafffundabout
T. Thayaparan, Marana Chiu, David R. Themens

Bibliographic record

VenueIEEE Geoscience and Remote Sensing Letters · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMeteorological Phenomena and Simulations
Canadian institutionsDefence Research and Development Canada
FundersDefence Research and Development Canada
KeywordsOver-the-horizon radarPolarRadarRemote sensingGeologyHorizonRadar trackerComputer scienceTelecommunicationsAstronomyPhysics

Abstract

fetched live from OpenAlex

Recent studies have highlighted the frequent occurrence of Sporadic-E (Es) layers—thin, localized zones of enhanced electron density—especially in high-latitude and polar regions. To address this, a new statistical model for Es has been incorporated into the Empirical Canadian High Arctic Ionosphere Model (E-CHAIM). The impact of Es on high-frequency (HF) radio wave propagation is examined using three-dimensional ray tracing. This study aims to evaluate how Es layers affect key radar parameters for Over-the-Horizon Radar (OTHR) systems. The results indicate that Es layers can significantly improve signal propagation by establishing additional, stable, and usable propagation paths, particularly during nighttime hours when these paths would otherwise not be available. As a result, a broader range of frequencies can be utilized for transmission. Additionally, the shift in reflection height from the F-region to the Es layer necessitates lower elevation angles for OTHR operations, as radar waves must be directed at shallower angles to reach their intended targets.

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 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 score0.308
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.023
GPT teacher head0.251
Teacher spread0.228 · 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.

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

Citations0
Published2025
Admission routes3
Has abstractyes

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