Near-field diagnostics of small printed antennas using the equivalent magnetic current approach
Bibliographic record
Abstract
A near-field to far-field transformation based on the antenna representation by equivalent magnetic current (EMC) sources has been proposed and validated experimentally on large high-directivity antenna arrays. In this paper, the use of EMC is extended to the diagnostics of low-directivity printed antennas. The limitation of the near-field to far-field transformation applied to EMC models of low-directivity antennas, caused by the finite dimensions of the antenna ground plane, is demonstrated. A method to partially overcome this limitation by including the contribution of diffracted rays is implemented, and its effectiveness is demonstrated with antenna prototypes. It is shown that the agreement between the far-field patterns measured in an anechoic chamber and the patterns computed from the EMC model obtained from the near-field measurements is significantly improved upon, within a sector of /spl plusmn/90/spl deg/ with respect to the antenna boresight in the E plane. The influence of the near-field sampling density and topology of the EMC model on the accuracy of the predicted far-field pattern is examined.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".