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Record W4404967701 · doi:10.1049/mia2.12535

Frequency‐diverse aperture imaging using an open cavity with a rough base

2024· article· en· W4404967701 on OpenAlexaff
Ehsan Rashidi‐Ranjbar, J. Rashed‐Mohassel, Mojtaba Dehmollaian

Bibliographic record

VenueIET Microwaves Antennas & Propagation · 2024
Typearticle
Languageen
FieldEngineering
TopicMicrowave Imaging and Scattering Analysis
Canadian institutionsSafe Engineering Services & Technologies (Canada)
Fundersnot available
KeywordsOpticsAperture (computer memory)WidebandScatteringSquare (algebra)Radiation patternRange (aeronautics)Ground planePhysical opticsCorner reflectorPhysicsAntenna (radio)AcousticsMathematicsGeometryComputer scienceMaterials scienceTelecommunications

Abstract

fetched live from OpenAlex

Abstract This paper proposes a single‐shot computational imaging using a new frequency‐diverse aperture, an open‐ended cavity with a rough surface base. First, it shows that scattering from a conducting rough surface made of conducting cones placed at random positions on a conducting ground plane, normally illuminated by an ultra‐wideband horn antenna (working in the 2–20 GHz range) provides random patterns with a frequency correlation function (FCF) width of Δ f , about hundreds of MHz. Next, by introducing four conducting walls placed around the rough surface, it obtains a higher number of spatially uncorrelated radiation patterns and a narrower FCF width of about Δ f /10, tens of MHz. To approximate the radiation patterns and measurement matrices in the numerical simulations, the geometrical optics (GO) approximation is used taking into account multiple interactions. On the other hand, to estimate them in practice, a trihedral corner reflector installed on an XYZ positioning table is employed. Finally, the image of a planar object with the shape of plus is reconstructed using the minimum least‐squares technique. The paper shows that for a 0.81 square metre image size, a decent‐focused image with a pixel size of about 0.81/400 square metres (about 5 cm × 5 cm) is realisable by using 400 frequency samples within the frequency range of 2–20 GHz.

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 categoriesMeta-epidemiology (narrow)
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 score0.945
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 communication0.0010.001
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 head0.021
GPT teacher head0.254
Teacher spread0.234 · 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.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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