Two-dimensional adaptive processing for ionospheric clutter mitigation in High Frequency Surface Wave Radar
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
High Frequency Surface Wave Radar (HFSWR) is a technology used for over-the-horizon detection of ocean vessels. This radar exploits the diffraction of electromagnetic waves around the curved surface of the Earth. To minimize the attenuation of the diffracted waves, the radar must operate at frequencies in the lower part of the high frequency (HF) band. However, radar signals at these frequencies also reflect from the Earth's ionosphere, which leads to radar clutter at ranges beyond 200 km. The linear broadside receive arrays used by conventional HFSWR systems cannot filter out this clutter as the arrays do not have any resolving power in elevation angle. Reported here are experimental investigations of the clutter suppression capability of one- and two-dimensional HFSWR adaptive processors. Three configurations are compared: one-dimensional spatial adaptive processing, two-dimensional spatial adaptive processing, and space-time adaptive processing. In all cases the number of adaptive degrees of freedom is 16. It is found that the best results are achieved by two-dimensional spatial adaptive processing, where a processing gain of up to about 20 dB can be achieved.
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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 | 0.000 | 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 | 0.000 | 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