Results and analysis of hybrid bistatic SAR experiments with spaceborne, airborne and stationary sensors
Bibliographic record
Abstract
Bistatic SAR is a promising and useful supplement to a classical monostatic SAR system. Since transmitter and receiver are spatially separated, additional information of a scene may be provided. Further, as shadowing, layover, and foreshortening depend on the bistatic geometry, which can be quite different to the monostatic case, they can contribute to image analysis and classification. The transmitter and receiver are located on different platforms, which may either be close together or hundreds of kilometers apart. Typical platforms are satellites, UAVs, aircrafts, and towers. This paper presents recent bistatic SAR experiments with spaceborne, airborne, and stationary sensors, which have been conducted at FHR or in cooperation with Defence Research & Development Canada. Image results are presented and analyzed with respect to scattering behavior and resolution and compared to monostatic images.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".