Pseudorange Multipath Mitigation By Means of Multipath Monitoring and De-Weighting
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The management of pseudorange multipath in GPS software processing ranges from total ignorance of the phenomenon to complex schemes for the estimation of the multipath signal. The former can cause significant parameter estimation degradation and the latter cannot necessarily provide accurate estimates. Therefore an alternative method is proposed here, which includes endeavouring to monitor the multipath signal and deweight the affected observations based on a sentinel observable. The objectives of this approach are the removal of pseudorange multipath-induced position outliers and the reduction of positioning noise. A modified version of the pseudorange minus carrierphase observable has been identified in the literature as a possible monitoring observable, and this linear combination is used in our technique. A straightforward, analytical de-weighting function based on this observable is introduced. The relationships between the observable and other weighting criteria such as carrier-to-noise density ratio and satellite elevation angle are also discussed.
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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