An Approach to Speed up Single-Frequency PPP Convergence with Quad-Constellation GNSS and GIM
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Bibliographic record
Abstract
The single-frequency precise point positioning (PPP) technique has attracted increasing attention due to its high accuracy and low cost. However, a very long convergence time, normally a few hours, is required in order to achieve a positioning accuracy level of a few centimeters. In this study, an approach is proposed to accelerate the single-frequency PPP convergence by combining quad-constellation global navigation satellite system (GNSS) and global ionospheric map (GIM) data. In this proposed approach, the GPS, GLONASS, BeiDou, and Galileo observations are directly used in an uncombined observation model and as a result the ionospheric and hardware delay (IHD) can be estimated together as a single unknown parameter. The IHD values acquired from the GIM product and the multi-GNSS differential code bias (DCB) product are then utilized as pseudo-observables of the IHD parameter in the observation model. A time varying weight scheme has also been proposed for the pseudo-observables to gradually decrease its contribution to the position solutions during the convergence period. To evaluate the proposed approach, datasets from twelve Multi-GNSS Experiment (MGEX) stations on seven consecutive days are processed and analyzed. The numerical results indicate that the single-frequency PPP with quad-constellation GNSS and GIM data are able to reduce the convergence time by 56%, 47%, 41% in the east, north, and up directions compared to the GPS-only single-frequency PPP.
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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 | 0.000 | 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 it