Fast versus slow scan radar operation for coherent small target detection in sea clutter
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
Small maritime surface targets can be difficult to distinguish from sea clutter in radar backscattered signals, but discrimination may be improved by using coherent detectors within the dwell time of a scanning radar. Non-coherent integration, coherent integration, the Kelly detector and the adaptive linear quadratic detector are considered. Target detectability may also be improved by combining the results of a single dwell across multiple scans. Overall target detection times of 2, 5 and 10 s are considered and the trade-off between within-scan dwell time and multiple scan processing gain is investigated. Analysis of high-range-resolution coherent X-band data of small boats reveals that faster scan rates with corresponding shorter dwell times provide improved target detection performance over slower scan rates and longer dwell times.
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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 | 0.001 |
| 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