Benefit of Partial L2C Availability for Correcting Ionospheric Error for Standalone GPS
Bibliographic record
Abstract
In this paper, the possibility of using partial availability of L2C signals to provide an ionospheric correction for the other single frequency satellites is investigated. Consideration is only given to standalone users. The available dual-frequency measurements are used to determine a zenith ionospheric error estimate that is then used to generate slant ionospheric corrections for each of the L1 C/A pseudorange measurements. The resulting corrections are then compared to those obtained with the broadcast ionosphere model and International GNSS Service (IGS) generated zenith ionosphere values. The corresponding position solutions are also compared to the uncorrected L1 C/A code position solution, and the position solution obtained by using the broadcast model. Results are assessed for the case when one, two or three L2C satellites are in view in order to determine if the number of satellites significantly affects results. Results presented are obtained from a large set of real data collected using a dual-frequency front-end in conjunction with the University of Calgary GSNRxTM software receiver and are applicable to any user capable of tracking the L1 C/A and L2C civil signals. The paper concludes with a discussion of the application of this principle to carrier phase processing, which is an area of ongoing research. Although the analysis focuses on a partial L2C constellation, the results will be important with the upcoming launches of Galileo and Compass as well as during the phase in of L5.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".