Development of an intelligent and hybrid scheme for rapid INS alignment
Bibliographic record
Abstract
Abstract Inertial navigation systems (INS) have been widely applied in many applications, such as precise positioning, navigation and guidance. Generally speaking, the initial attitude angles between the body and navigation frames are estimated during the INS alignment process using an optimal estimator such as the Kalman filter. Due to measurement errors, the Kalman filter takes about up to fifteen minutes to converge. In this article, a hybrid scheme integrating an Adaptive Neuro‐Fuzzy Inference System with the Kalman filter is proposed to achieve a faster and more accurate alignment process. The preliminary results indicate that a faster alignment with superior accuracy can be achieved through the use of the proposed scheme. Key words: INSalignmentKalman filterANFIS Notes Corresponding author. (Tel: 886–6–2370876 ext. 829; Fax: 886–6–2375764; Email: kwchiang@mail.ncku.edu.tw)
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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".