Single Point Positioning Using GPS, GLONASS and BeiDou Satellites
Bibliographic record
Abstract
This paper introduces the Chinese BeiDou satellite system and its comparison with the actual completed American GPS and the Russian GLONASS systems. The actual BeiDou system consists of 14 satellites covering totally the Asia-Pacific area. A Single Point Positioning (SPP) test has been realised in Changsha, Hunan province, China, to show the advantage of using combined pseudorange solutions from these 3 satellite navigation systems especially in obstructed sites. The test shows that, with an elevation mask angle of 10°, the accuracy is improved by about 20% in horizontal coordinates and nearly 50% in the vertical component using the simultaneous observations of the 3 systems compared to the GPS/GLONASS solution. For the processing with an elevation mask angle of 30°, most of the time less than 4 GPS satellites were available for the GPS-only case and no solution was possible. However, in this difficult situation, the combined GPS/GLONASS/ BeiDou solutions provided an accuracy (rms values) of about 5 m.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".