Vehicular Navigation in Urban Canyons Using a High Sensitivity GPS Receiver Augmented with a Low Cost Rate Gyro
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Bibliographic record
Abstract
A vehicular navigation system that consists of an unaided high sensitivity GPS receiver integrated with a vehicular navigation quality piezoelectric vibrating gyro is presented. First, the performance of the stand-alone high sensitivity GPS receiver in urban canyons is studied and the motivation for the gyro augmentation is given. Experimental testing was performed in downtown Calgary. GPS raw data analysis was carried out using an epoch-by-epoch least squares approach to better analyze the quality of the measurements and their impact on positions. These results are compared to those obtained using a filtered solution. Rate gyro augmentation model equations and Kalman filter equations with additional constraints used herein are then described. The results of receiver augmentation with a rate gyro show significant improvement in accuracy in where GPS receivers experience harsh signal masking and severe multipath.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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