A videoSAR mode for the x-band wideband experimental airborne radar
Bibliographic record
Abstract
DRDC has been involved in the development of airborne SAR systems since the 1980s. The current system, designated XWEAR (X-band Wideband Experimental Airborne Radar), is an instrument for the collection of SAR, GMTI and maritime surveillance data at long ranges. VideoSAR is a land imaging mode in which the radar is operated in the spotlight mode for an extended period of time. Radar data is collected persistently on a target of interest while the aircraft is either flying by or circling it. The time span for a single circular data collection can be on the order of 30 minutes. The spotlight data is processed using synthetic apertures of up to 60 seconds in duration, where consecutive apertures can be contiguous or overlapped. The imagery is formed using a back-projection algorithm to a common Cartesian grid. The DRDC VideoSAR mode noncoherently sums the images, either cumulatively, or via a sliding window of, for example, 5 images, to generate an imagery stream presenting the target reflectivity as a function of viewing angle. The image summation results in significant speckle reduction which provides for increased image contrast. The contrast increases rapidly over the first few summed images and continues to increase, but at a lesser rate, as more images are summed. In the case of cumulative summation of the imagery, the shadows quickly become filled in. In the case of a sliding window, the summation introduces a form of persistence into the VideoSAR output analogous to the persistence of analog displays from early radars.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.130 | 0.037 |
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".