On the characterization of reflective surfaces using dual-polarization GNSS-R

Abstract

Global navigation satellite systems reflectometry (GNSS-R) is a technique to extract information from reflecting surfaces by the reflected GNSS signals. GNSS-R has garnered increasing attention in the scientific literature due to its continuous global coverage and its superior spatial resolution. Moreover, operating in the L-band renders GNSS-R relatively immune to adverse weather conditions and affords high sensitivity to soil electrical properties. This work introduces a new approach with a dual-polarization antenna, left-hand circular polarized (LHCP) and right-hand circular polarized (RHCP), receiving the reflected signal from a sufficiently smooth surface so that all reflected energy arrives from the specular reflection point. The objective is to characterize the reflecting surface by extracting the relative permittivity and conductivity from the reflected signal. In contrast to other studies found in the literature, the reflection of the GNSS signal on different materials, including dielectric and conductive materials is considered. We derive a maximum likelihood estimator (MLE) for estimating the dielectric parameters of the reflective surface and other parameters of the reflected signal. We also derive the respective Cramer–Rao Lower Bound (CRLB) evaluating the performance of the MLE. The attained results are assessed based on the signal-to-noise ratio (SNR) and the angle of reflection of the reflected signal, which are the parameters that predominantly influence the proposed approach. Lower elevation angles, for instance, lead to higher estimation accuracy, while for reflective surfaces composed of metallic materials a higher SNR is needed to yield favorable estimation performance. Regarding dielectric materials, the estimation results are encouraging and thus enable diverse remote sensing applications by GNSS-R using the proposed setup.