Investigation on the Effect of GPS and GLONASS Constellation Use on the Accuracy of Point Positioning in PPP Method
Bibliographic record
Abstract
After the completion of the GLONASS (GLObalnaya NAvigatsionnaya Sputnikovaya Sistema or GLObal NAvigation Satellite System) which was developed by Russian Federation and making it service as second running system all over the world after GPS, satellite based geodetic studies have been focused on integration of GPS and GLONASS systems. It is possible to determine the position and/or increase the accuracy and reliability by receiving more data from the satellites especially for the forested lands, urban canyons, open mine areas and valleys etc. which have inadequate number of satellites or weak signals. Nowadays, development in satellite technology and dazzling progress in data processing and analysis allows to point positioning within cm to dm level with only a single GNSS receiver. It is possible to make positioning by using the method called as Precise Point Positioning (PPP) in static or kinematic mode using precise orbit and clock data without being in need of any data other than collected with a single receiver. Until recently, PPP-derived coordinates were obtained by only scientific GNSS processing software but now it is possible to obtain a result with the software that universities or institutes coded or commercial software. However, all these programs require GNSS knowledge and generally requires licensing fee. Recently, many on-line PPP processing services which eliminates the disadvantages and have practical usage have been started to be used. One of these services, CSRS-PPP(Canadian Spatial Reference System-Precise Point Positioning) attracts attention with its accuracy and ease of use. In this study, static measurements were performed with the receivers which can collect data from GPS and GLONASS satellite systems at the geodetic points from intense residential areas in Çorum city region, mostly around the city center. Collected data was evaluated separately by GPS and by GPS+GLONASS integrated systems with CSRS-PPP service operated by Canada. The PPP-derived coordinates were compared with the ones obtained by differential method (accepted as accurate coordinates). In order to investigate the effect of Rapid and Final precise products (with have different latency) on the result, the data was uploaded to the system after finishing the measurements and again just after several weeks, and the results were compared. In this study, the test procedure and obtained results are discussed. Keywords : GPS, GLONASS, Precise Point Positioning (PPP), CSRS-PPP, on-line PPP.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".