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Record W2136882717

Discrimination of subsurface targets with a plane of symmetry using polarimetric bistatic radar

2004· article· en· W2136882717 on OpenAlexaff
Michael W. Phelan, Joe LoVetri

Bibliographic record

VenueInternational Conference on Grounds Penetrating Radar · 2004
Typearticle
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsBistatic radarPolarimetryClutterReflection symmetryPlane symmetrySignature (topology)PhysicsSymmetry (geometry)Ground-penetrating radarGround planePlane (geometry)AzimuthRadarOpticsComputer scienceRemote sensingRadar imagingGeologyAntenna (radio)GeometryScatteringMathematicsTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

The so called vampire signature effect introduced by Baum [I][2] whereby the monostatic backscattered fields measured from a point on the target symmetry plane exhibit no cross-polarized response in the far field is extended to the case of bistatic measurements in the near field. The principle is applied to GPR in a series of polarimetric SAR measurements to differentiate between buried landmines, which are generally geometrically symmetric, and random clutter, which is generally asymmetric. A method is proposed to utilize the vampire signature as a feature to enhance GPR images to achieve landmine detection. The method is applicable to targets that possess one or more planes of symmetry when both transmit and receive antennas are located on the symmetry plane. Experimental results taken in a controlled sand-box environment are shown to verify the proposed method and the receiver operating characteristic (ROC) for the method is shown.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.037
GPT teacher head0.291
Teacher spread0.254 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2004
Admission routes1
Has abstractyes

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Same venueInternational Conference on Grounds Penetrating RadarSame topicGeophysical Methods and ApplicationsFrench-language works237,207