Perancangan Antena Mikrostrip Dual Band Profil Rendah Menggunakan Teknik DGS Dan Meander Line Untuk Aplikasi GNSS
Bibliographic record
Abstract
Some of the parameters that are considered to measure GNSS antenna performance are polarization, polarization, bandwidth, return loss and antenna dimensions. This study aims to design a low profile dual band microstrip antenna using the Defected Ground System (DGS) and Menader Line (ML) techniques for GNSS applications. In this research, the DGS technique is used to increase the bandwidth while the ML technique is used to reduce the antenna dimensions. This antenna design uses a FR4 Epoxy substrate with a thickness of 1.6 mm. To design and analyze the antenna, the CST Studio Suite 2016 simulator is used. The simulator is equipped with an optimizer feature that can optimize antenna parameters. Based on the design results, an antenna with a size of 183.6 x 183.6 x 1.6 mm3 has been produced. The antenna works in dual band, namely in the band 1247 - 1294 MHz (bandwidth - 3.70% BW) for radio navigation satellite services Glonass (G2) and Galileo (E6). And in the band 1539-1606 MHz (4.26% BW) for the Galileo (E1) flight radio navigation service, Compass and GPS (L1). Keywords: Global Navigation Satellite System (GNSS), low-profile dual-band microstrip antenna, Defected Ground System (DGS) dan Meander Line (ML).
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".