Dynamic Metasurface Antenna-Based Mills-Cross Aperture for 3-D Computational Microwave Imaging
Bibliographic record
Abstract
This work presents a computational imaging (CI) system capable of retrieving 3-D images of the area under inspection. The system is based on the use of two linear dynamic metasurface antennas (DMAs) specifically designed and fabricated for this purpose. The developed DMAs are able to generate the spatially-incoherent radiation patterns (or measurement modes) required by CI systems to compress the scene information by reconfiguring their radiating apertures. This reconfiguration is achieved by tuning the unit cells that populate themonandoffusing p-i-n diodes. The two DMAs are arranged in a Mills-Cross configuration, which enables to synthesize a 2-D effective aperture and, as a result, to reconstruct 3-D radar images. The performance of the proposed system has been experimentally validated, showing its capability to retrieve high quality images of different targets with a low clutter level. Furthermore, the impact of the number of masks (i.e., sets of tuning states of the diodes) on the quality of the radar images has been evaluated both qualitatively and quantitatively.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".