Ship Detection, Discrimination, and Motion Estimation via Spaceborne Polarimetric SAR-GMTI
Bibliographic record
Abstract
A new approach to ship detection, discrimination, and motion estimation is proposed and demonstrated using a combined polarimetry and GMTI technique from a spaceborne platform. Using a standard dual-pol SAR, the new method exploits a bright “shadow” in cross-pol imagery of a moving ship and its azimuth-shifted image to discriminate it from other stationary or quasi-stationary objects (e.g., icebergs) on the ocean surface and to estimate its motion parameters, such as radial speed and heading. The motion estimation results are compared to those obtained using the newly implemented Dual-Channel Polarimeric GMTI modes on RADARSAT-2. Unlike the ship wake approach, the proposed technique is applicable to and successfully demonstrated for both C-band and X-band radars (RADARSAT-2 and TerraSAR-X) and it is not dependent on the angle of incidence to achieve a good signal-to-clutter ratio and ship detectability. Physical mechanisms giving rise to ship “shadows” are also discussed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".