Three Attitude Models and their Characterization in the Generic Multisensor Integration Strategy for Kinematic Positioning and Navigation
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
This research aims at further completing our novel Generic Multisensor Integration Strategy (GMIS) with the systematic development of three alternate attitude models, i.e., roll-pitch-heading (RPH), direction cosine matrix (DCM), and quaternion. The GMIS' potential for a true sensor level data fusion is leveraged to its full extent here by facilitating comprehensive error analysis framework in Kalman filtering. A comparative analysis between the solutions resulted from the GMIS associated with each attitude model have been analysed and compared through real road test data. The attitude models were found to perform very consistently, exhibiting the same behaviours in the residuals of the process noise and measurement vectors along with the estimated variance components. Besides, an analysis was conducted to investigate how each attitude model reacts to a sudden trajectory variation captured by the IMU. Each attitude model still performed consistently, but the DCM model in particular exhibited resistance to absorbing erroneous observations into its process noise estimates.
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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