A Ku-Band Compact Offset Cylindrical Reflector Antenna with High Gain for Low-Earth Orbit Sensing Applications
Bibliographic record
Abstract
The rise of CubeSats has unlocked opportunities for cutting-edge space missions with reduced costs and accelerated development timelines. CubeSats necessitate a high-gain antenna that can fit within a tightly confined space. This paper is primarily concerned with designing a compact Ku-band offset cylindrical reflector antenna for a CubeSat-based Earth Observation mission, with the goal of monitoring Arctic snow and sea ice. The development of a Ku-band offset cylindrical reflector, with a compact aperture of 110 × 149 mm2 (6.3λ × 8.5λ), is described alongside a patch array feed consisting of 2 × 8 elements. The patch array feed is designed using a lightweight Rogers substrate and is utilized to test the reflector. Adopting an offset configuration helped prevent gain loss due to feed blockage. Analyzing the reflector antenna, including the feed, thorough simulations and measurements indicates that achieving a gain of 25 dBi and an aperture efficiency of 52% at 17.2 GHz is attainable. The reflector’s cylindrical shape and compact size facilitate the design of a simple mechanism for reflector deployment, enabling the antenna to be stored within 1U. The array feed and reflector antenna have been fabricated and tested, demonstrating good consistency between the simulation and measurement outcomes.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".