Ship GPS Multipath Detection Experiments
Bibliographic record
Abstract
Ship multipath caused by the surrounding ship superstructure and water is a significant error source that can severely limit the reliability of GPS-derived navigation solutions. This is especially important given the low reliability of many current marine receivers (MacGougan and Liu, 2002). The magnitude of code multipath aboard a Canadian Coast Guard vessel was assessed using a series of onboard measurements with three receivers using different levels of correlator technology and two different antennas. The antennas were successively located on the upper mast of the ship. The three receivers tested consisted of a standard marine receiver, a high quality receiver set to use wide correlator methods and a high grade receiver using an advanced correlator technology. A fixed base station with known coordinates was used to accurately determine the reference position of the ship during the tests using differential carrier-phase measurements. Then, a residual analysis from a single differenced positionconstrained least-squares solution was performed in order to isolate pseudorange error whose main component is multipath. The data was collected over several days while the ship was in port in a static position. This enabled the detection and analysis of repeated day-to-day multipath. Two kinematic experiments were also conducted to study the differences with the static case.
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) | 0.000 | 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".