Design of a High-Power Gaussian Pulse Transmitter for Sensing and Imaging of Buried Objects
Bibliographic record
Abstract
This paper aims to investigate a high-power and low-cost monopulse transmitter circuit for underground and underwater sensing and imaging. The transmitter utilizes two Marx transistor-based pulse generators, a balun, and a Vivaldi antenna. A simple output network, including an inductor and Schottky diode, is employed to compensate for the ringing level and distortion and improve the pulse width. The ringing level of the developed circuit is around 6 percent. The output is a Gaussian pulse with pulse width and amplitude of 481 ps and 50 V, respectively. In order to have a high amplitude monopulse, an exact replica of this network in parallel is exploited. The outputs of the parallel circuits are subtracted through the balun to have adc-free monopulse with amplitude and pulse width of 26 V and 483 ps, respectively. The monopulse is radiated by a Vivaldi antenna toward a buried object. The image of the target is generated using the time-domain global back projection (TD-GBP) method. Three imaging experiments are conducted to verify the functionality of the designed sensor system. The reconstructed images and the reference images are shown high structural similarity indexes of 98.6%, 95.4%, and 97.6%.
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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) | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".