Statistical Characteristics of Linear-Polarization GNSS Interferometric Reflectometry and Its Application for Observing Sea State

A novel basic observable, termed the alternating-current texture (ACT), is defined from the original linear-polarization carrier-to-noise ratio (CNR) of the Global Navigation Satellite System (GNSS) for monitoring wind vector. The amplitude distribution (AD), autocorrelation function (ACF), power spectral density (PSD), and fractal dimension (FD) of the ACT are explored. The results show that these statistical characteristics derived from the GNSS–Interferometric Reflectometry (GNSS-IR) CNR resemble those directly extracted from the reflected signal. Twelve statistics from the AD, ACF, PSD, and FD, as observables sensitive to wind speed, are analyzed. The findings suggest that these statistics exhibit geometric dependence, especially at the low elevation angle. Furthermore, the skewness of the AD, the correlation time of the ACF, PSD peak, PSD width, and FD respond more effectively to wind speed than other statistics, and are used to assess the capability of retrieving wind speed. Kernel principal component analysis (KPCA) is employed to fuse these statistics to produce a new sensitive observable to wind speed. When elevation and azimuth angles are confined to optimal regions with minimal interference, a root mean square error (RMSE) of 1.57 m/s is obtained with a minute-level temporal resolution. In contrast, a geodetic GNSS receiver provides an RMSE of 2.55 m/s. In addition, based on the anisotropy of the sea surface, the feasibility of these statistics in retrieving wind direction is investigated. Novel sensitive observables to wind direction, derived from the best-fit ellipse to the spatial distributions of the statistics, are defined. The fusion using KPCA achieves the best determination coefficient (DC) of 0.50 with wind direction, while the geodetic receiver yields a DC of only 0.16. These results conclude that low-cost GNSS sensors can be utilized for retrieving wind vector, and the linear-polarization GNSS-IR outperforms its right-handed circular polarization (RHCP) counterpart.