Investigations into the quality of final-product dual-frequency static PPP over fixing time using CSRS-PPP free online service: GPS Vs. GPS + GLONASS
Why this work is in the frame
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Bibliographic record
Abstract
The Global Positioning System (GPS) delivers precise, continuous, and globally accessible positioning and timing information through satellite-based measurements. Nevertheless, relying on a single satellite constellation imposes limitations related to satellite availability and geometric distribution, which can adversely affect the reliability of positioning, particularly in environments where visibility is reduced or satellite geometry becomes suboptimal. This study examines the performance of static Precise Point Positioning (PPP) as a function of fixing time using the Canadian Spatial Reference System Precise Point Positioning (CSRS-PPP) service under two processing scenarios: GPS-only and GPS+GLONASS. The analysis was conducted under open-sky conditions where multipath effects are negligible. Dual-frequency GNSS data were collected from ten spatially well-distributed stations, each observed continuously for 24 hours. Static PPP solutions were generated for fixing intervals beginning at 1 hour and incrementally increasing to 24 hours. The 24-hour static PPP solution served as the reference for evaluating the accuracy and stability of all other solutions. The results show that utilizing GLONASS observations alongside GPS leads to notable improvements in solution reliability and overall positioning stability throughout the fixing intervals. These benefits are particularly clear during shorter observation durations, especially the first one hour where the absolute errors in N, H, 2D and 3D are reduced by (2.2, 3, 1.8 and 2.22 cm) with GPS+GLONASS, respectively. As for the Easting component, the absolute errors determined from the two constellations are very tiny and rounded about zero. The benefits of adding GLONASS to GPS can also be noted during the first several hours when PPP solutions are most sensitive to satellite geometry and convergence behavior. Although the enhancement in mean absolute positional accuracy becomes marginal for longer observation periods, the multi-constellation configuration significantly reduces the occurrence of outliers and decreases the dispersion of coordinate residuals across the Northing, Height, 2D, and 3D components. The results demonstrate that even under optimal open-sky conditions, where multipath is virtually absent, the integration of GLONASS contributes measurably to improving the robustness and reliability of Static PPP. In summary, although the improvement of integrating GLONASS with GPS in static PPP in the average absolute accuracy is marginal after long fixing time comparing to GPS-alone, the benefits are significant for the first a few hours, specially the first fixing hour where the 3D quality obtained via one-hour static dual-frequency PPP with GPS+GLONASS can be reached after 3 to 4 hours fixing time using GPS-alone.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it