Numerical and Experimental Assessment of Source Reconstruction for Very Near-Field Measurements With an Array of $H$ -Field Probes
Bibliographic record
Abstract
This paper presents a novel formulation of the source reconstruction problem that aims at increasing the accuracy of near-held (NF) to far-held (FF) transformations in a particular measurement arrangement, where the NF data are rapidly acquired by a planar array of H-held probes located close to a ground plane. A source reconstruction algorithm is proposed for obtaining the near electric and magnetic helds as well as the FF radiation pattern of the antenna under test after hltering the effects of the currents induced on the ground plane backing the probe array. This algorithm exploits a system of integral equations that, after discretization according to the method of moments, enables backprojecting the measured helds on equivalent sources distributed over an arbitrary 3-D surface. Different integral equations are considered for that purpose. The accuracy provided by four different integral formulations is investigated from measured and synthetic experimental data and compared with the standard plane wave spectrum reconstruction technique, making it possible to arrive at a conclusion as to which one to use in order to make the hnal analysis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".