On the Use of a Metasurface Lens Over a Large-Element-Spacing Antenna Array for Grating Lobe Suppression and Gain Enhancement
Bibliographic record
Abstract
The large-element-spacing (LES) antenna arrays have the advantages of low cost and less structural complexity but generally suffer from high-level grating lobes. In this paper, we propose a new method to address the issue. By placing a metasurface lens above such an LES array at an appropriate height to adjust and compensate for the phases of the near fields generated by the array, the grating lobes can be suppressed or eliminated without increasing the design complexity. Theoretical analyses, calculations from an efficient numerical method, simulations, and experiments are carried out to validate the proposed method. A complete study of the radiation performance of the proposed antenna configuration is also conducted using the above different ways. All the results demonstrate that the grating lobes from an LES antenna array can be suppressed and the gain can be improved by the proposed method at the cost of a slight increase in the antenna array profile or volume. The novel approach can be applied to any LES antenna arrays, with either large or small sizes, uniform or non-uniform spaces, and periodic or aperiodic structures.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".