Mitigating tropospheric propagation delay errors in precise airborne GPS navigation
Bibliographic record
Abstract
The high spatial and temporal variability of the troposphere is well known, as is its effect-through propagation delays-on GPS positioning. This effect can be particularly problematical in airborne kinematic differential positioning where the altitude difference between reference station and aircraft is typically quite large. The use of zenith delay models and mapping functions at ground stations is fairly well understood, however their use for processing data collected on board aircraft is less well understood. Previous tests have indicated that some of the models often used for navigation purposes (e.g. Altshuler, NATO and the proposed WAAS model) perform poorly compared to those generally used for static positioning. These tests were not done under kinematic conditions however, but as comparisons with ray tracing through radiosonde data. This paper outlines the work recently done at UNB on testing the reliability of tropospheric models in precise airborne GPS navigation. Particular attention has been paid to the performance of the currently proposed WAAS model. The data used to test the models is from an adverse weather flight dynamics experiment undertaken off Newfoundland, Canada, in March 1995. The paper includes an analysis of the GPS flight data to determine the influence of different tropospheric models on the reliability and accuracy of the solutions.
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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".