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 them <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on</small> and <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">off</small> using 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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".