Small Footprint Multilayered Millimeter-Wave Antennas and Feeding Networks for Multi-Dimensional Scanning and High-Density Integrated Systems
Bibliographic record
Abstract
This paper overviews the state-of-the-art of substrate integrated waveguide (SIW) techniques in the design and realization of innovative low-cost, low-profile and low-loss (L3) millimeter-wave antenna elements, feeding networks and arrays for various wireless applications. Novel classes of multilayered antenna structures and sys-tems are proposed and studied to exploit the vertical di-mension of planar structures to overcome certain limita-tions in standard two-dimensional (2-D) topologies. The developed structures are based on two techniques, namely multi-layer stacked structures and E-plane corners. Differ-ent E-plane structures realised with SIW waveguide are presented, thereby demonstrating the potential of the proposed techniques as in multi-polarization antenna feeding. An array of 128 elements shows low SLL and height gain with just 200g of the total weight. Two versions of 2-D scanning multi-beam are presented, which effectively combine frequency scanning with beam forming networks. Adding the benefits of wide band performance to the multilayer structure, two bi-layer structures are investigated. Different stacked antennas and arrays are demonstrated to optimise the targeted antenna performances in the smallest footprint possible. These structures meet the requirement for developing inexpensive compact millimeter-wave antennas and antenna systems. Different structures and architectures are theoretically and experimentally studied and discussed for specific space- and ground-based appli-cations. Practical issues such as high-density integration and high-volume manufacturability are also addressed.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".