Direct Determination of Angular Velocity Using GPS
Bibliographic record
Abstract
Controlling a ship in a berthing operation is carried out mainly by the change of state, such as velocity and yaw rate (turn rate), although the value of the change of state is very small at berthing. Very high precision is, therefore, required to determine the velocity and angular velocity. A sensor that has an accuracy of ±0.02°/s (1 σ) is sought for determination of turn rate in a berthing system. Three-dimensional angular velocity can directly be determined, with 2 independent baselines of 3 GPS antennas, using instantaneous Doppler measurements or phase rate (temporal difference of phase) observations. This paper discusses the mathematical model for direct determination of angular velocity using GPS, and the comparison of the results of the angular velocity determination using the Doppler and phase rate. The precision of angular velocity determination is estimated using temporal difference of the attitude sensors (TSS and gyrocompass) on board a hydrographic sounding ship. The RMS values of the difference of yaw rate determination between the two systems were: ±0.16°/s using phase rate and ±0.31°/s using Doppler measurements with the separation of onboard antennas of ca. 1·34 m. 10 m baselines could satisfy the sensor requirements for angular velocity determination during berthing maneuvers.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".