Arbitrary-Angle Squint-Free Beamforming in Series-Fed Antenna Arrays Using Non-Foster Elements Synthesized by Negative-Group-Delay Networks
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Bibliographic record
Abstract
Beamforming in series-fed antenna arrays can inherently suffer from beam-squinting. To overcome the beam-squinting problem, low-dispersion, fast-wave transmission lines can be employed. Such transmission lines can be designed by loading a regular transmission line with non-Foster reactive elements (e.g., negative capacitors and inductors). As a result of a recent development, these non-Foster reactive elements can be implemented using loss-compensated negative-group-delay (NGD) networks, providing a solution to the stability issues associated with conventional non-Foster networks. In this work, transmission lines augmented by loss-compensated NGD networks, representing the non-Foster reactive-element loading, are employed for designing wideband fast-wave, low-dispersion transmission lines. This work consolidates this non-Foster reactive element loading method with earlier efforts where NGD networks were used to implement zero-degree phase shifters for beamforming at the broadside direction, and generalizes these methods for arbitrary-angle beamforming from backfire to endfire including the broadside direction. Experimental results are presented for a wideband linear four-element transmitting array feed network for beamforming at 30° with respect to the broadside direction in the frequency range 1-1.5 GHz. By connecting this feed network to four wideband tapered-slot antennas, the beamforming performance is experimentally verified inside an anechoic chamber. Moreover, the antenna array is experimentally tested for transmission of a narrow pulse, where low distortion is observed at the beamforming angle over the entire operating bandwidth. The physical length of the feed network is realistic and is 0.96 wavelengths long at the center of this frequency range. In addition, switched-line phase shifters are employed for squint-free beamforming in three other angles: 60°, 0°, and $-30^{\circ}$.
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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 | 0.000 |
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 it