A General Method for the Calibration of the C-band Convair-580 SAR
Bibliographic record
Abstract
A general polarimetric model which includes systems whose receiving configuration is independent of the transmitted polarization (one configuration), as well as systems with two distinct receiving configurations, was introduced in [9]. This model was used to develop a calibration method for early X-band polarimetric SAR developed at Canada Centre for Remote Sensing (CCRS) [9]. A simplified method was adapted for the C-band SAR system that is equipped with polarization switches with high isolation (better than 50 dB) [4], [2]. This method leads to an accuracy of 1 to 2 dB in radiometry and 5°in phase, for incidence angles within ±20°from the antenna boresight angle. Tests run on various data sets lead to the conclusion that the Convair-580 SAR system is quite stable in short-term, but is not over the long-term. This requires the deployment of reference point targets during each flight. On the other hand, several data sets demonstrated the existence from time to time of a significant cross-talk term. It is shown that the general calibration method of [9] can still be applied to retrieve pure polarizations from the distorted measurements, and provide an assessment of the system distortion matrix during data acquisition.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.006 |
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".