Estimating polarization purity with noise
Kostinski, A., Kestner, D., Vivekanandan, J.. (2024). Estimating polarization purity with noise. IEEE Transactions on Geoscience and Remote Sensing, doi:https://doi.org/10.1109/TGRS.2024.3380531
| Title | Estimating polarization purity with noise |
|---|---|
| Genre | Article |
| Author(s) | A. Kostinski, D. Kestner, Jothiram Vivekanandan |
| Abstract | We formulate a problem of estimating and monitoring mismatch (unwanted departure from orthogonality) of two ostensibly orthogonal polarization channels in a fully polarimetric general device such as a polarimetric weather radar. A statistical approach is proposed by using thermal noise or, more generally, a "polarimetric noise" class of sources. The suitable noise class of distributions is shown to be rooted in the complex multivariate Gaussian probability density function (pdf), the latter possessing a uniform pdf on the Poincare sphere (PS), with a probability measure given by a fractional surface area. To that end, we develop a parameter to estimate polarization purity. By relating an inner (dot) product of noisy electric fields to their cross-correlation coefficient, we arrive at a simple relation between the ellipticity delta( varepsilon;) and tilt delta(tau) mismatches and the measured complex voltage cross-correlation coefficient rho : rho approximate to -/+ cos(2 varepsilon;)delta(tau)+/- i delta( varepsilon;) . Our results are confirmed by Monte Carlo simulations. Thermal noise microwave data collected by the S-band radar of the National Center for Atmospheric Research (NCAR) during solar calibration scans is used to set bounds on delta( varepsilon;) and delta(tau) , thereby characterizing polarization purity. |
| Publication Title | IEEE Transactions on Geoscience and Remote Sensing |
| Publication Date | Jan 1, 2024 |
| Publisher's Version of Record | https://doi.org/10.1109/TGRS.2024.3380531 |
| OpenSky Citable URL | https://n2t.org/ark:/85065/d7xp794k |
| OpenSky Listing | View on OpenSky |
| EOL Affiliations | RSF |