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Record W2546775350 · doi:10.1109/lgrs.2016.2618855

First-Order Bistatic High-Frequency Radar Power for Mixed-Path Ionosphere-Ocean Propagation

2016· article· en· W2546775350 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Geoscience and Remote Sensing Letters · 2016
Typearticle
Languageen
FieldEngineering
TopicRadar Systems and Signal Processing
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBistatic radarClutterRadarIonosphereRadar horizonRemote sensingRadar imagingGeologyComputer scienceGeophysicsTelecommunications

Abstract

fetched live from OpenAlex

A theoretical mixed-path ionospheric clutter model for bistatic high frequency radar is presented. Based on previous monostatic work, the first-order received electric field for bistatic radar is derived by considering the scattering processes on both the ionosphere and the ocean surface. Then, the first-order received power model is developed by incorporating a vertically polarized pulsed dipole antenna. In order to investigate the power spectrum of this ionospheric clutter model and its relative intensity to that of the ocean clutter, a normalized ionospheric clutter power is simulated. Numerical simulation results are compared with that of monostatic radar looking at the same ocean scattering patch. Subsequently, the simulations show how the bistatic angle and the ionospheric conditions affect the power spectrum for this bistatic mixed-path ionosphere clutter.

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: Empirical · Consensus signal: none
Teacher disagreement score0.838
Threshold uncertainty score0.514

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 communication0.0000.000
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 head0.006
GPT teacher head0.192
Teacher spread0.186 · 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