Music-Enhanced CFAR for High Frequency Over-the-Horizon Radar
Why this work is in the frame
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Bibliographic record
Abstract
To increase the number of location options for an HF surface-wave radar (HFSWR) there is significant interest in reducing the physical size of the receive array. Reducing the aperture results in a degradation of both sensitivity and azimuth information. Azimuth accuracy may be retained by the use of high-resolution methods (such as MUSIC) that have a significantly smaller beamwidth than standard beamforming. It is expected that the application of these high-resolution methods will help retain azimuth information with reduced aperture size. This paper evaluates the effects of reducing the physical aperture of the linear receive array used in HFSWR and using post-detection azimuth re-estimation by high-resolution methods to maintain azimuth resolution, accuracy, and hence tracking performance. This paper is limited to evaluating the effect of increased azimuth beamwidth and does not address the issue of reduced radar sensitivity. Data for the evaluation was obtained from an HFSWR system located at Cape Race, Newfoundland, Canada. The accuracy of the detection centroid for a full 16-element array is compared to the accuracy for a half-aperture 8-element array. It is shown that similar accuracy can be achieved from the shortened array employing the MUSIC-Enhanced CFAR compared to the full size array using the conventional CFAR processing.
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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 | 0.000 |
| 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