2-in-1 Smart Panels: Embedding Microstrip Patch Antennas within Satellite Structures
Bibliographic record
Abstract
The increasing commercialization of small-space requires versatile subsystems that make efficient use of limited spacecraft volumes. Smart structure technology that provides both mechanical and electrical functionality is a beneficial solution to spacecraft miniaturization. Embedding avionics within satellite structural components reduces the overhead required for integrating numerous systems and maximizes space for the payload and other critical instruments. Combining different subsystems that are usually developed independently of each other is an innovative approach to space system design. This paper evaluates the feasibility of an embedded microstrip patch antenna within a structural panel comprised of a sandwich structure of carbon fiber composites and a polyethylene fiber composite. Patch antennas provide a low profile, light weight, small-dimension and easily-manufactured solution to small satellite communication. The embedded antenna panels are designed to be adaptable for any function and size required by the end user. This paper presents three distinct applications for this embedded antenna technology: (1) An S-band antenna for space-to-earth telemetry transmission for a radar mapping spacecraft; (2) An S-band antenna for space-to-ground communications for CubeSats; and (3) A Ka-band antenna for space-to-space communications between nanosatellites in a low-Earth orbit backhaul constellation. For each case, we present technical performance evaluation (including electromagnetic simulation using ANSYS HFSS) and a study of the systems integration feasibility.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".