Filter-Bank-Enabled Leaky-Wave Antenna Array Technique for Full-Band-Locked Radar System in Stitched Frequency-Space Domain
Bibliographic record
Abstract
Inspired from the filter-bank (FB) concept that is normally used for multirate signal processing, an FB-enabled array technique of leaky-wave antennas (LWAs) is proposed and studied for creating full-band-locked frequency-scanning radar systems in a stitched frequency-space domain. This is mainly for addressing the coupling dilemma between the range and angle resolutions that is historically and naturally inherited from a conventional frequency-scanning radar. FB-related conditions for the required "frequency-space stitching" (or full-band beam-target illumination) in radar operation are described and translated into the design specifications of an array of LWAs, such as engineered beam-scanning functions, beam-crossovers, and phase alignments. For a direct proof of concept, a practical two-channel LWA array is modelled, fabricated, and measured. Simulated and measured results are in a reasonable agreement, which exhibit the highly desired "frequency-space stitching" behaviour. The proposed FB-enabled array solution may present a potential competitor against the prevailing phased array.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".