Simulation of the Impact of Low-Earth-Orbit GNSS on Carrier Phase Ambiguity Resolution
Bibliographic record
Abstract
This paper details the impact that a Low-Earth-Orbit (LEO) constellation will have on existing GNSS carrier phase ambiguity resolution. A LEO constellation was modelled to have 66 satellites at an altitude of 780km and was used together with GPS satellites to conduct a global covariance simulation and evaluate the performance of a combined low- and medium-earth orbit system compared to GPS alone. The LEO satellites were found to improve how quickly the system could reach 99.9% probability of correct fix by a factor of 2.4 on average. Additionally, a detailed look at an example where a LEO satellite disappears early in the dataset emphasizes how strongly the system can be affected by the fast-changing geometry of a single LEO satellite. Overall, this leads to the conclusion that current GNSS systems will be well complimented by future LEO GNSS, and that LEO satellites will be beneficial to positioning applications without requiring full global coverage with redundancy.
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".