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Record W4416790622 · doi:10.1016/j.ifacol.2025.11.218

Design of a Game-Theoretic Guidance Law for Leader-Follower Aircraft with Target Estimation

2025· article· en· W4416790622 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIFAC-PapersOnLine · 2025
Typearticle
Languageen
FieldEngineering
TopicGuidance and Control Systems
Canadian institutionsArtificial Intelligence in Medicine (Canada)
FundersNational Natural Science Foundation of China
KeywordsControl theory (sociology)Terminal guidanceContext (archaeology)Kalman filterLinearizationState (computer science)Nonlinear systemTerminal (telecommunication)Feedback linearizationFilter (signal processing)

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.691
Threshold uncertainty score0.713

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.223
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it