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Record W2127897753 · doi:10.1109/aps.1997.625552

Extraction of near-surface index of refraction using radar phase measurements from ground targets

2002· article· en· W2127897753 on OpenAlexaff
Frédéric Fabry, C. Frush, Isztar Zawadzki, Alamelu Kilambi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGNSS positioning and interference
Canadian institutionsMcGill University
Fundersnot available
KeywordsRadarCalibrationRefractive indexPhase (matter)Range (aeronautics)RefractionOpticsPhysicsMeasure (data warehouse)Remote sensingGeodesyGeologyComputer scienceMaterials scienceTelecommunications

Abstract

fetched live from OpenAlex

The authors consider the simplest radar equation involving the index of refraction n: the time t taken by electromagnetic waves to reach a target at range r and return to the radar is r=2rn/c/sub 0/, with c/sub 0/, being the speed of light in a vacuum. For fixed targets, r is constant and only n varies; hence if t could be measured precisely for such targets, the average value of the refractive index over the path between the radar and these targets could be determined. Unfortunately, most radars cannot measure t and site surveys are not accurate enough to determine r with the part-per-million accuracy required to obtain useful information about n. However, if the range to the target is fixed, but only known to a fair accuracy, say better than 1%, it would be enough to allow us to relate changes in t to changes in n; the absolute calibration would then have to be done by other means. With this scheme, we are only required to determine changes in t that can be obtained by measuring the phase of the target.

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)0.000
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: Empirical
Teacher disagreement score0.499
Threshold uncertainty score0.566

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)0.0010.000

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 head0.068
GPT teacher head0.283
Teacher spread0.216 · 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 designBench or experimental
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

Citations5
Published2002
Admission routes1
Has abstractyes

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