GPS-denied Navigation: Attitude, Position, Linear Velocity, and Gravity\n Estimation with Nonlinear Stochastic Observer
Bibliographic record
Abstract
Successful navigation of a rigid-body traveling with six degrees of freedom\n(6 DoF) requires accurate estimation of attitude , position, and linear\nvelocity. The true navigation dynamics are highly nonlinear and are modeled on\nthe matrix Lie group of SE2(3). This paper presents novel geometric nonlinear\ncontinuous stochastic navigation observers on SE2(3) capturing the true\nnonlinearity of the problem. The proposed observers combines IMU and landmark\nmeasurements. It efficiently handles the IMU measurement noise. The proposed\nobservers are guaranteed to be almost semi-globally uniformly ultimately\nbounded in the mean square. Quaternion representation is provided. A real-world\nquadrotor measurement dataset is used to validate the effectiveness of the\nproposed observers in its discrete form. Keywords: Inertial navigation,\nstochastic system, Brownian motion process, stochastic filter algorithm,\nstochastic differential equation, Lie group, SE(3), SO(3), pose estimator,\nposition, attitude, feature measurement, inertial measurement unit, IMU.\n
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".