Robust mitigation of multipath and ionospheric delays in multi-GNSS real-time kinematic (RTK) receivers
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Bibliographic record
Abstract
In this paper, we develop a new scheme for RTK positioning using multi-constellation GNSS measurements in presence of multipath and ionospheric delays. The proposed procedure for multi-frequency ambiguity resolution is based on four steps: 1) at each epoch, a Gaussian sum particle filter is used to track the user position and the float ambiguity solution adaptively to the dynamic environment by minimizing the noise level and estimating the ionospheric errors ; 2) we utilize a new carrier phase multipath indicator to reject integers candidates that are affected by multipath errors, 3) we apply LAMBDA method to search the integer ambiguities; and finally 4) validate the fixed solution using a robust statistical test. Real-data test results show the effectiveness of the overall developed procedure for long-baseline RTK positioning.
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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