Autonomous underwater vehicle localization using the acoustic tracking system
Bibliographic record
Abstract
Operator peace-of-mind during Autonomous Underwater Vehicle (AUV) missions is dependent on the ability to localize the vehicle. During launch and recovery phases this capability is particularly important. Defence R&D Canada (DRDC) Atlantic has designed and built a long-range tracking system for the International Submarine Engineering Explorer class AUVs. The acoustic tracking system (ATS) enables an operator on a loud icebreaker platform to determine the position of the AUVs at ranges up to 30 km. An acoustic projector, mounted on the AUV, emits a hyperbolic frequency modulated (HFM) chirp at a preset time interval. A small, directional, acoustic receiving array mounted near the stern of the icebreaker, accurately synchronized with the remote projector, receives signals from the distant AUV. Matched filter processing is used to determine the time of flight of the transmitted chirp. A beamforming algorithm applied to the data provides bearing and elevation angle estimates for the received signals. A ray tracing algorithm then uses this information, along with the sound velocity profile, to determine the position of the AUV. Moreover, ATS uses different HFM chirps to provide a basic one-way AUV state messaging capability. We conclude with a brief discussion of ATS data collected during in-water trials.
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 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 | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".