Bibliographic record
Abstract
This article reports further progress in developing an active-loaded Rotman lens reflector for radar cross section (RCS) enhancement. Although the Rotman lens has been employed in backscattering applications, its passive performance imposes gain constraints when it comes to RCS improvement. In the novel structure we present, the lens is outfitted with custom-designed low-power reflection amplifiers to enable overall system gain amplification and modulation. An array of printed-Yagi antennas has been added to the lens, and the monostatic RCS pattern of the lens antenna has been measured. The lens antenna exhibits a nearly uniform RCS pattern between -35 and 35 degrees at 5.3 GHz in both active and passive modes. The active lens structure demonstrates a 5.5 dB increase in RCS while loaded with 11 amplifiers with a ≈6.5 dB gain. The active reflector consumes only ≈1.2 mw of power. Due to its high gain, wide angular coverage, and low power consumption, this structure is ideally suited for low-power RCS enhancement applications, such as mm-wave automotive radar sensors.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".