Phase correction techniques for reducing errors due to edge diffraction in reflectarray
Bibliographic record
Abstract
Phase correction due to finite reflectarray (RA) antenna size and edge diffraction (ED) is proposed. The process is based on the numerical full wave analysis. The edge diffraction is mainly caused because of amplitude and phase ripples at sharp knife-edges of the outer perimeter of the RA antenna. The diffracted fields at the edges is diffracted in all directions resulting in disturbing the original phase and amplitude distribution, which further affect the pre-expected performance of the antenna. This could cause increasing of sidelobe level (SLL) and reducing aperture efficiency. The degradation in the antenna performance can be reduced by using serrated-edge ground, slotted GND and rolled-over edges with corner blended ground plane in the bottom of RA. The proposed methods provide RA performance when compared with RA antenna using sharp knife-edge (KED) ground plane. The proposed methods are analyzed by designing 19*19 RA antenna in fullwave analysis in the Ka-Band using size varying multi-bowtie radiating elements. The antenna performance is evaluated based on the achieved gain, aperture efficiency, SLL, and cross polarization. The proposed technique's result are compared with original RA using knife-edge ground plane. The best antenna performance is obtained using rolled-over edges GND plane. The antenna provides maximum gain of 26.36 dB, aperture efficiency of 59.5 %, SLL of -17.1 dB and 1-dB gain bandwidth of 11.2%, evaluated at center frequency 30 GHz. Near field analysis is also done for phase correction authentication.
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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".