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Record W2534937481 · doi:10.1109/icia.2005.1635043

A method for constructing the observer trajectory in bearings-only tracking of targets with a markovian model

2006· article· en· W2534937481 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicTarget Tracking and Data Fusion in Sensor Networks
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTrajectoryParameterized complexityTracking (education)Control theory (sociology)Observer (physics)Moment (physics)Range (aeronautics)Constant (computer programming)Computer scienceMarkov processBaseline (sea)MathematicsAlgorithmArtificial intelligenceEngineeringPhysicsControl (management)Statistics

Abstract

fetched live from OpenAlex

We propose a method for constructing the observer trajectory in bearings-only tracking. This method is applicable to any target with a Markovian model but in particular, we study it for nearly-constant velocity targets. The proposed method is built upon a family of optimal trajectories obtained for the localization of stationary targets. These trajectories can be parameterized by a parameter known as range-to-baseline ratio. For moving targets, at each moment, the range-to-baseline ratio is computed and the appropriate trajectory is pursued based on this ratio and current estimates of the target bearing and course. We study the behavior of this method by simulation.

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)0.001
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: Methods
Teacher disagreement score0.548
Threshold uncertainty score0.400

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.020
GPT teacher head0.254
Teacher spread0.233 · 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