Design of a Game-Theoretic Guidance Law for Leader-Follower Aircraft with Target Estimation
Bibliographic record
Abstract
In the context of a game-theoretic scenario involving an hypersonic gliding vehicle equipped with a defender and an interceptor during the glide phase, a game-theoretic guidance law has been developed, taking into account target estimation. By establishing a nonlinear model for three-body confrontation, linearization and model order reduction based on zero-control miss distance are conducted. A time operator is introduced to unify the terminal time, and the guidance law is derived based on optimal control theory. By utilizing extended Kalman filtering for the state estimation of the interceptor, the filtering results are applied to the guidance law designed in this paper. Simulation results indicate that, under the condition of detection information regarding the ‘line-of-sight angle with the interceptor’ for the hypersonic gliding vehicle and the defensive units, the state estimation error of the interceptor by the filter is acceptable, and the terminal miss distance of the interceptor by the defensive units is approximately 1.45 m.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".