Design and Development of a High-Power Pulse Transmitter for Underground Environmental Perception
Bibliographic record
Abstract
This article represents a design for a high-power pulse transmitter for high-depth imaging applications. The pulse transmitter consists of an avalanche transistor-based pulse-shaping network, an improved step recovery diode (SRD)-based configuration, and a pulse-shifting circuit with a broadband combiner to generate a first derivative Gaussian pulse for high-power applications. The output pulse of the transistor-based circuit is fed to a balun, which produces two opposite polarity pulses and then feeds two parallel SRD pulse-shaping circuits that produce ultrashort pulses. The SRD-based part of the circuit was developed to have a high amplitude output pulse. Moreover, using a technique based on pulse shifting, a higher power monopulse was achieved without using a balun and a differentiator. This design achieved a monopulse of 169-ps pulsewidth with a peak power of$P =5.78$W. In order to check the validity of the transmitter for imaging applications, several experiments for buried objects in the sand are conducted, including metal objects, water pipe, rock, and copper veins. All reconstructed 3-D images clearly represent the target shape and dimension, confirming the functionality of the designed transmitter for sensing and imaging applications.
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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) | 0.003 | 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".