Low-Cost 3D printed Dielectric Hyperbolic Lens Antenna for Beam Focusing and Steering of a 79GHz MIMO Radar
Bibliographic record
Abstract
Extensive research has been conducted on millimeter wave (mm-wave) chipset solutions led to reduction in size and cost while adding sensitivity and accuracy. Recent 79GHz chipset solutions using antenna-in package approach were developed for various applications with a wide beamwidth and low gain. However, for some applications such as multiple people vital signs detection and corridor gait monitoring, there is still a need to achieve higher gain with thinner beamwidth, to increase the signal-to-noise ratio (SNR) and the transmit/receive range of the system, mitigate the reflection from surrounding objects as well as reduce multi-path effects. The use of a lens is an appealing solution since it could improve the system performances while using existing chipset solution. Using low cost and rapid manufacturing 3D printing technology, we designed and fabricated a dielectric lens antenna for a 79GHz MIMO radar. Compared with the system without lens, the full-wave simulation demonstrated a 14dB improvement in gain which is in good agreement with measurement results.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".