Effects of time dispersion on echo, reverberation, and echo to reverberation ratio in a range-dependent Pekeris waveguide
Bibliographic record
Abstract
In shallow water, active sonar performance is typically limited by reverberation, making the prediction of target echo and reverberation, and their ratio, an important part of sonar performance prediction. In range-dependent shallow water environments, these quantities are often calculated without considering the effect of dispersion. The effect of time dispersion is considered taking examples for a range-dependent bathymetry from the 2010 Weston Memorial Workshop. Using the analytical method of [M. A. Ainslie and D. D. Ellis (in press), IEEE Journal of Oceanic Engineering], combined with normal mode predictions [D. D. Ellis (1995). The Journal of the Acoustical Society of America, 97(5), 2804-2814], neglect of time dispersion is found to result in an error of up to 16 dB in the echo level for a short CW pulse (duration 3 ms). The effect of 3D geometry is considered, and results for a cylindrically symmetric bathymetry are shown to differ by up to 14 dB from the corresponding results with a Cartesian symmetry. The difficulties associated with modeling an LFM pulse are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".