Active Retrodirective Rotman Lens Antenna for Wide-Angle RCS Enhancement
Bibliographic record
Abstract
This paper presents measurement results and analysis of an innovative active retrodirective Rotman lens antenna architecture, designed to enhance the radar cross-section (RCS) for backscattering applications. Unlike conventional passive retrodirective systems, our design integrates custom-designed reflection amplifiers to significantly boost backscattered signal gain while maintaining low DC power consumption. A novel biasing technique enables independent phase and gain control of the amplifiers, ensuring a uniform array response and reducing DC power consumption by approximately 30%. Experimental monostatic RCS measurements at 5.15 GHz with a linearly polarized incident wave demonstrate a uniform RCS response over a ±40° scan angle. The integration of reflection amplifiers enhances backscattering, allowing the lens to maintain a consistent −0.5 dB RCS across the entire scan angle, which is 9 dB higher than the average RCS of a metal plate with the same effective aperture. The compact design (approximately <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$6\lambda \times 6\lambda $ </tex-math></inline-formula>) and ultra-low power consumption (approximately 0.19 mW) make this system well-suited for low-power radar applications, such as mm-wave automotive radar sensors. These results confirm the feasibility of active-loaded phase conjugating systems for high-performance backscattering applications.
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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 | 0.000 | 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".