GPS signal fading model for urban centres
Bibliographic record
Abstract
The use of GPS receivers in wireless telephones has been proposed as a means of automatically identifying the position of wireless 911 callers. GPS simulators are an efficient means of testing the accuracy of such technology but require a channel model for GPS satellite signals. This paper presents a methodology for measuring and modelling the fading distribution of GPS satellite signals received in outdoor urban centres. GPS fading data, as collected in the downtown areas of Calgary and Vancouver, Canada, are used to generate fade histograms as a function of satellite elevation angle. These histograms are found to be sufficiently similar between the two cities and, therefore, lead to the conclusion that a generic fade distribution for urban centres is reasonable. Parameters for the Urban Three-state Fade Model are estimated from the empirical fading data collected in each city. Correlation between the model parameters derived for each city is significant and also suggests that a generic model may be derived. The parameters from the two cites are averaged to produce a generic Urban Three-state Fade Model, which adequately represents the fade histograms of each city. These averaged parameters generally agree with parameters derived from data collected in Tokyo, Japan.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".