<title>Simple method for modeling radar reflections in a homogeneous halfspace, with applications</title>
Bibliographic record
Abstract
We have developed a method to rapidly compute synthetic radar records from complex reflecting surfaces. The approach is a 3- D time domain Hemholtz-Kirchhoff (HK) representation, similar to Hilterman (1981), that includes the radiation characteristics of GPR dipoles on the surface of a uniform dielectric halfspace. Validity is established by making comparisons with published model results and by comparisons with field data. Comparison to the ray theory results of Zeng et al. (1997) show excellent agreement in reflection arrival times for pipes of various diameters. We also reproduce the non-specular reflection results of Schleicher et al. (1991), which show that large amplitude reflections can originate from the inflection points of curved surfaces. Our comparisons with field data use reflection records taken at a test site in Borden, Ontario, over horizontally oriented buried metal drums. The H-plane reflection data were collected using shielded 700-MHz dipoles. Our raw synthetic amplitude trends show reasonable agreement to the field data, but are not perfect. Using a small diameter synthetic dipole array, we show that the mismatch is most likely caused by antenna shielding effects. The versatility of the HK method is demonstrated by giving results for a number of interesting applications. These include synthetic records for crisscrossing pipes buried at various depths, reflection synthetics from a truncated cone representing the slag heaps in Daniels and Brower (1998), and reflections from a rough surface. The slag heap models demonstrate the effect of antenna polarization on reflections from sloping surfaces. Analysis of synthetic reflections from rough surfaces shows that the coda following the first impulsive arrival can be used to estimate the surface roughness. This is of interest for interpreting reflections from glacier data. Our results demonstrate that the HK method is useful in interpreting data, as well as for developing field survey strategies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.043 | 0.029 |
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".