An adaptive GLR estimator for state estimation of a maneuvering target
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Bibliographic record
Abstract
This paper presents a novel adaptive generalized likelihood ratio (A-GLR) state estimator applied to rapidly maneuvering targets in pursuit-evasion scenarios. The A-GLR estimator employs a bank of adaptive models which is constructed and updated on-line. The state estimate is a probabilistic mixture of the model-matched estimates. The adaptation of the models, the model-matched estimates, and the a-posteriori probabilities of the models are calculated recursively by employing a previously developed adaptive-/spl Hscr//sub 0/ GLR algorithm. Numerical simulations of a maneuvering target (a ballistic missile) show that the A-GLR estimator delivers state estimates characterized by a smaller average error and a smaller covariance as compared with those obtained using the interacting multiple model (IMM) estimator.
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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 | 0.001 |
| 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