Results and Analysis of Using the MEDLL Receiver as a
Bibliographic record
Abstract
The Multipath Estimating Delay-Lock-Loop (MEDLL) is a method for mitigating the effects due to multipath within the receiver tracking loops. Recently the MEDLL receiver was modified to output the multipath parameters, hence the name ‘Multipath Meter’. These parameters include the delay, relative amplitude, and phase of the multipath signal along with the residual values for each correlator. The multipath parameters are estimated by the MEDLL and the residuals indicate the quality estimation process. This paper investigates how the Multipath Meter can be used in real-time monitoring of the GPS signal. Using a GPS simulator the MEDLL receiver is tested to determine how accurately the multipath parameters can be measured. Also, data is collected from an antenna location on the roof of the NovAtel facility at Calgary, Alberta, Canada. Two specific situations are focused on: short delay and long delay multipath. Results show that the Multipath Meter is useful for signal quality monitoring and reference site surveys.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".