Scattering Matrix Retrieval Using Full-Polarimetric GNSS-R

This article presents the mathematical background and modeling for full-polarimetric Global Navigation Satellite System Reflectometry (GNSS-R) receivers for nonnegligible cross-polar component in the scattered signal. A signal model is presented to retrieve the Stokes parameters using the Mironov model to estimate the soil surface’s dielectric constant. This article compares data collected by the SMAP-Reflectometry (SMAP-R) receiver and the proposed signal model, emphasizing the need to consider the cross-polar component ( $S_{\mathrm {hv}}$ ). Simulations obtained without considering the cross-polar component have poor agreement in all Stokes parameters. A model is implemented using a complex cross-polar component resulting in notable improvements in the bias and unbiased root mean square difference (ubRMSD) between the modeled and measured SMAP-R Stokes parameters. Furthermore, a methodology is proposed for estimating the $S_{\mathrm {hv}}$ component using SMAP-R and a soil moisture (SM) reference dataset. An analysis of $S_{\mathrm {hv}}$ reveals a moderate correlation with vegetation water content (VWC) and surface roughness ( $\sigma _{\mathrm {slp}}$ ). We developed an SM model by estimating $S_{\mathrm {hv}}$ using both VWC and $\sigma _{\mathrm {slp}}$ , showing the potential of full-polarimetric GNSS-R to provide SM estimates upon proper characterization of the cross-polar component. Results show the ubRMSD of 0.09 m3/m3 with respect to the in situ soil moisture network (ISMN). Finally, this study establishes that an RMSD better than 0.02 when estimating $S_{\mathrm {hv}}$ is required for an SM product accuracy better than 0.07 m3/m3 for polarimetric GNSS-R SM retrievals.