Visibility of LEO Satellites under Different Ground Network Distributions
Bibliographic record
Abstract
The Low Earth Orbit (LEO) satellites have shown various benefits in augmenting the Positioning, Navigation and Timing (PNT) service based on Global Navigation Satellite Systems (GNSSs). The higher number of LEO satellites and their much smaller footprints than those of the GNSS satellites motivate studies of the ground tracking network design to pursue higher visibilities to LEO satellites. This contribution proposes an algorithm, called here ‘MaxVis’ to select network stations for LEO satellites of different inclinations and altitudes. The goal is to increase the general visibility and shorten the visibility gaps of LEO satellite that can be observed from the entire ground network, i.e., when at least one of the network stations are visible to the satellite. A parameter can be set to balance the priority of the two objectives. It was found that LEO satellites with high altitudes and low inclinations tend to deliver high visibility. With only the polar regions excluded from the design area for demonstration purposes, the general visibility could reach above 98% with less than 30 stations when the LEO satellite has an altitude of 1200 km and an inclination of 50 degrees. The visibility could be significantly reduced when island areas are excluded from the design area.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.011 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| 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; both teacher heads agree on what is shown here.
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".