Sidelobe apodization for high resolution of scattering centres in ISAR images
Bibliographic record
Abstract
Inverse synthetic aperture radar (ISAR) image processing is useful in identifying and isolating dominant scattering centres of a target for subsequent placement of radar absorbing material (RAM). ISAR image construction artifacts have the potential of obscuring low intensity scatterers in the image as well as blurring regions where closely separated scatterers occur. Spatially variant sidelobe apodization (SVA) is a technique that reduces sidelobe levels in a Fourier image while maintaining the image resolution that would be obtained using the rectangular window. We investigate the application of 2 versions of SVA to the ISAR image of a ship; these are the standard cosine-on-pedestal SVA and the new Kaiser window version of SVA. It is found that either SVA approach is able to find and isolate scattering centres. We also found that when polar reformatting is required, neither SVA version is a substitute for it, but applying SVA after polar reformatting gives excellent results.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".