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Record W3087888546 · doi:10.1109/tmtt.2020.3023095

UWB Sensor Characterization for Radar Sensing and Imaging in Superluminal Propagation Regions

2020· article· en· W3087888546 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 Transactions on Microwave Theory and Techniques · 2020
Typearticle
Languageen
FieldEngineering
TopicMicrowave Imaging and Scattering Analysis
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSuperluminal motionRadarRadar imagingContinuous-wave radarOpticsInverse synthetic aperture radarPhysicsTransmitterRadar engineering detailsSynthetic aperture radarField (mathematics)AcousticsRemote sensingComputer scienceGeologyTelecommunications

Abstract

fetched live from OpenAlex

This article investigates the pulse propagation in the near field of a transmitter and reflector from the perspective of radar sensing and imaging. The peaks of the radiated and reflected pulses were found to have traveled at superluminal speeds in the near field of radar. The conceptual explanation and experimental demonstration of the unique properties of the radiated and reflected pulses and their impact on near field radar imaging are presented in this article. To confirm the superluminal propagation, in this study, we considered several ultrawideband (UWB) sensors and scatterers. The physics behind the superluminal propagation and pulse shape change in the radar near field is demonstrated using the Huygens principle, and a method to improve the imaging of radar in the near field while using synthetic aperture techniques is also proposed.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.723
Threshold uncertainty score0.696

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 head0.009
GPT teacher head0.211
Teacher spread0.202 · 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