A harmonic spectral beamformer for the enhanced localization of propeller-driven aircraft
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.
Bibliographic record
Abstract
The following paper presents several array processing techniques that may be used to enhance the localization of acoustic source targets, such as UAVs. A review of common methods is first provided, followed by several algorithms developed to reduce computational loads for the application of concern. A beamforming method is proposed that exploits the properties of harmonic narrowband signals, such as that generated by propeller-driven aircraft to enhance direction of arrival accuracy. In addition, a regional contraction search algorithm is proposed to minimize computational loads associated with the presented localization technique. A brief comparison of the proposed method to that of standard frequency domain beamformers is also provided using both theoretical analysis and experimental data. For the case of target localization between two moving fixed-wing UAVs, it was found that the proposed harmonic spectral beamforming method increased localization accuracy by 50% over the standard steered response power approach.
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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 | 0.001 | 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 | 0.001 | 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