Unidirective Miniaturized Ultrawideband Antenna for Sensing Buried Objects in Handheld Ground-Penetrating Radar Systems: A design approach
Bibliographic record
Abstract
Ground-penetrating radars (GPR) using ultrawideband (UWB) technology have attracted a lot of research interests worldwide for high-resolution sensing and material characterization. This research contribution, therefore, introduces a miniaturized lightweight UWB antenna with high-gain characteristics for applications in handheld GPR systems. The high-gain antenna is developed to function in the 3.13–11.74-GHz wide frequency range such that it can allow high-resolution sensing of buried targets, such as landmines, metal pipes, and other structures. An elliptical quadrant-shaped UWB monopole radiator with a protuberant ground plane is conceptualized to constitute a highly miniaturized antenna of size${18}\,{\times}\,{11}\,{\text{mm}}^{2}$. The standalone UWB antenna realizes an impedance bandwidth of 3.07–11.67 GHz with a peak gain of 2.9 dBi. Next, a single-side copper-coated dielectric substrate as a reflector is placed beneath the antenna to attain a significant gain improvement. The proposed design with a reflector provides an average gain improvement of about 7.1 dB without influencing the original bandwidth. For experimental validation, a prototype is fabricated and characterized. The measured performance reveals close agreement with the simulation with an operating bandwidth of 3.19–11.83 GHz and a maximum gain of approximately 10 dBi at 4.02 GHz.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".