Coherent ground mapping of polar format images with applications to high-resolution wide-area SAR imaging
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Bibliographic record
Abstract
In this article, we consider some approaches to using the polar format algorithm for high-resolution wide-area synthetic aperture radar (SAR) imaging. We will broadly discuss two general approaches to extending the polar format algorithm to produce focused high-resolution imagery over wide areas. First, we will describe a fast backprojection-like algorithm based on coherently mapping polar formatted subapertures to the ground and coherently combining the ground-mapped images. Second, we will discuss an alternative approach to generating high-resolution wide-area imagery, which starts with an initial polar format image and then subsequently refines the image in subpatches in a coherently consistent manner across the image. Central to both methods is a general framework for coherently mapping polar format images to the ground.
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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