Design, Simulation, and Performance Analysis of an INS/GPS System using Parallel Kalman Filters Structure
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Bibliographic record
Abstract
Thanks to the strong growth of MEMS technology, the Inertial Navigation System (INS) is widely applied to navigation and guidance of moving objects. However, there exist errors in the inertial sensor’s signals that cause unacceptable drifts. To minimize these effects on the INS system, a GPS is usually employed simultaneously with an INS in order to increase the dimension of the system; the desired parameters are estimated by Kalman filtering technique applied to the enlarged system. In this paper, we present the design, simulation and performance analysis of an INS/GPS system using two parallel Kaman filters in order to increase the accuracy of the parameter estimation process. The results show that this system could be efficiently brought to practical applications.
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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