Robust STAP for HFSWR in dense target scenarios with nonhomogeneous clutter
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Bibliographic record
Abstract
Space-time adaptive processing (STAP) algorithms generally address interference, whether homogeneous or not, and are tested in environments with a single target or with targets that do not interact with each other. However, a high frequency surface-wave radar (HFSWR) monitoring off-shore activity likely sees many targets closely spaced in angle, Doppler and range. Target detection in HFSWR is further complicated by the nonhomogeneous sea clutter. In this paper we develop a two-stage STAP algorithm, based on the previously developed fast fully adaptive (FFA) approach, for the dense target scenarios of interest. The proposed algorithm is tested on measured data provided by Raytheon Canada. Our results show that the modified FFA scheme is able to detect targets not seen by the current scheme used to generate the provided track data.
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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