Performance evaluation of low-cost GPS systems for static and kinematic applications
Bibliographic record
Abstract
This thesis looks at improving positional accuracy of low-cost systems by investigating a method to isolate the multipath error based on wavelet analysis. Several sets of static and kinematic data were collected in different types of environment using a single-frequency GPS receiver. The code minus carrier combination of the GPS observables was exploited. After accounting for certain errors and resolving the ionospheric delay using ionospheric maps, the remaining terms were essentially multipath and noise. Wavelet analysis was then used to extract the multipath error. These approximations were utilized to identify and remove those satellites that were severely contaminated with multipath. Another approach investigated the subtraction of multipath approximations obtained by wavelet analysis from the corresponding code measurements. The positioning results of these two approaches were compared with those of the original data and assessed. For the static data sets, eliminating satellites contaminated with multipath proved to be most effective. For the kinematic sessions, neither of the two approaches displayed any improvement.
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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 | 0.000 | 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 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".