Simulation analysis of sea surface current extraction from microwave nautical radar images
Bibliographic record
Abstract
In this paper, an improved algorithm for extracting sea surface currents from X-band nautical radar image sequences is presented. The marine radar images are simulated by first numerically generating current-included ocean surface elevation maps for given sea states and radar parameters. Then the plan position indicator (PPI) radar images are produced via tilt and shadowing modulation processing. From the simulated radar images, current velocity is derived with a modified iterative least square (LS) fitting method in which higher harmonic wave components and aliasing effects are considered. Here, the correct current velocity is found by a proposed iteration-terminating criterion instead of using a fixed number of iterations. Simulated inversion results for a variety of current velocities and sea states validate the algorithm and show that the number of iterations may be reduced while obtaining highly precise measurement. The performance of the algorithm is also tested using real vertically polarized radar data through comparison with the results from other current methods and an acoustic Doppler current profiler (ADCP).
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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".