An algorithm for multitarget tracking with multiple asynchronous bearings-only sensors
Why this work is in the frame
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Bibliographic record
Abstract
An algorithm is developed for tracking multiple targets using distributed bearings-only sensors. It is assumed that the sensors report the measurements asynchronously and the processing is done centrally. The proposed algorithm first forms bearings-only (mono) tracks for each sensor and then combines them to form Cartesian position (stereo) tracks. The stereo tracks are initialized using a multidimensional assignment technique. Once the stereo tracks are initialized the mono tracks contributed to the stereo tracks are deleted and the stereo tracks are updated directly using the measurements from the sensors. As shown later in this paper the proposed algorithm is computationally simple and can provide better tracking performance compared to an existing algorithm. Simulations carried out to track multiple targets confirm the effectiveness of the proposed algorithm.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.005 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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