A combined sea clutter and noise model appropriate to the operation of high‐frequency pulsed Doppler radar in regions constrained by external noise
Bibliographic record
Abstract
In recent years, bistatic pulsed high‐frequency ground wave radar models of the ocean clutter have been developed. Several new features, distinct from earlier monostatic developments, appear as products of those analyses. One question that needs to be addressed is, “What characteristics of the theoretical clutter models are likely to be visible in experimental data collected from the ocean surface?” A major consideration in answering this question is the development of an appropriate noise model. Such a model along with an analogous clutter model is derived. This allows a simulation of time series data for both clutter and noise which may be treated using standard Fourier transform techniques to provide a periodogram for the typical combined noise/clutter spectrum of scattering from the ocean surface. The analysis proceeds on the assumption of an externally noise‐limited system, with the noise being characterized as a white Gaussian zero‐mean process. The aliasing due to noise undersampling is seen to be an integral part of the model. Statistical stationarity is assumed throughout. Both infinite and finite pulse trains are considered.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".