Requirement on Antenna Cross-Polarization Isolation for the Operational Use of C-Band SAR Constellations in Maritime Surveillance
Bibliographic record
Abstract
The issue of antenna cross-polarization isolation has been previously discussed for the design of fully polarimetric synthetic aperture radars (SARs). Dual-polarized antennas with cross-polarization isolation that is better than -30 dB are desirable for more convenient polarimetric data calibration since measurements of antenna crosstalk (magnitude and phase) variations with incidence angle are not required. For an antenna with significant polarization crosstalk, it is still possible to retrieve pure polarization measurements of HH, HV, VH, and VV provided that the four corresponding received voltages are measured. However, it is not possible to recover from cross-polarization contamination for single- or dual-polarization measurements. Therefore, it is important to set up a minimum requirement on dual-polarized antenna isolation so that single- and dual-polarization applications are not unduly affected. In this letter, the minimum requirement on cross-polarization antenna isolation is investigated for operational use of C-band SARs in maritime surveillance applications. Calibrated polarimetric RADARSAT-2 data are used to simulate single- and dual-polarization data with cross-polarization contamination for a dual-polarized antenna with cross-polarization isolation ranging from -20 to -35 dB. It is shown that the cross-polarization HV (or VH) channel can be significantly affected, particularly at steep incidence angles. As a result, key applications that require the use of pure HV, such as ship detection and wind-speed measurements, are significantly affected. A requirement for a minimum of -30-dB antenna isolation is established. Antennas with cross-polarization isolation better than -35 dB are desirable for reliable exploitation of HV data at steep incidence angles.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 0.001 |
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".