Registration of multi-frequency SAR imagery using phase correlation methods
Bibliographic record
Abstract
The advancing development of low-cost small spacecraft platforms enables Earth observation constellation missions using a variety of imaging methods, including multistatic (single-transmitter, multiple-receiver) interferometric synthetic aperture radar (InSAR). Image registration is a necessary step preceding interferometric analysis of multistatic or repeat-pass SAR imagery. An effective image registration method for a potential InSAR constellation mission must not incur errors from distortions caused by imaging geometry and temporal changes in the terrain, and should as well be applicable to multi-frequency SAR registration and potentially multi-modal registration with optical imagery. Furthermore, the ability to register and process images onboard the spacecraft is desirable due to power and downlink limitations on a small platform. Herein we demonstrate a frequency-domain registration method on single-frequency, repeat-pass, and dual-frequency SAR imagery, for use in a future small satellite remote sensing constellation.
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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".