Broadband and High-Gain Circularly-Polarized Antenna With Low RCS
Bibliographic record
Abstract
In this paper, a wideband circularly polarized (CP) antenna with a low radar cross section (RCS) and high gain properties is investigated. The proposed antenna is based on a combination of the Fabry-Perot cavity (FPC) and sequential feeding technique. The purpose of this antenna is to produce CP with high directive gain over a wide bandwidth while preserving low RCS. The principle of the FPC and resonance is achieved by applying one frequency selective surface (FSS) metasurface. A microstrip slot array operating at the Ka-band, excited by a sequentially rotated feeding network, is designed and fabricated. It is indicated that all the merits mentioned above can be obtained over a broad frequency band by designing a suitable FSS metasurface and modifying the feeding lengths to adjust desirable phase. RCS reduction is realized by 180° ±37° reflection phase variations between adjacent FSS unit cells on the metasurface. The experimental results show that the gain of the antenna with the metasurface is at least 7 dB greater than that of the primary antenna with a peak value approximately 20 dB at 28.5 GHz. In addition, bandwidths of 3-dB gain, impedance (|S11| ≤ -10 dB), and axial ratio ≤3 dB are ranged from 27.5 to 33.5 GHz (19.7%), 26.7 to 34.2 GHz (24.6%), and 26.8 to 33.1 GHz (21%), respectively. The monostatic RCS reduction for a normal incidence is effectively suppressed from 28 to 48 GHz (52%).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".