Imaging moving targets using the second-order keystone transform
Why this work is in the frame
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Bibliographic record
Abstract
The use of synthetic aperture radar (SAR) for moving target imaging has recently attracted a great deal of interest. The ability to obtain focused images of moving targets makes it possible to maximise the use of existing single-channel SAR systems, without upgrading to more complex and expensive multi-channel systems. In this study, a novel technique is presented for moving target imaging utilising a single-channel SAR operating in Spotlight mode. First, the second-order keystone transform is applied to remove range curvature. Next, a non-linear phase correction is applied to correct the remaining range walk. Finally, the nominally quadratic phase in azimuth is estimated and corrected to provide focused imagery. An experimental result is presented to demonstrate the performance of this approach.
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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