A two-antenna GNSS approach to determine soil moisture content and vegetation growth status

In land surface remote sensing using Global Navigation Satellite System reflectometry (GNSS-R) signals, it is common to observe signal coupling between the reflections from the soil surface and vegetation. But most recent research focuses on either bare soil or single vegetation. The vegetation significantly reduces the amplitude of the GNSS signal and increases the standard deviation (STD) of the carrier phase and pseudorange calculations. This study proposes a solution that uses GNSS transmission reflectometry (GNSS-TR) and wavelet transform to decouple signals reflected off vegetation-covered and bare soil surfaces. This coupling persists despite the ability of wavelet transform to initially separate the signal-to-noise ratio (SNR) sequences of GNSS reflected signals into different frequency components. This study uses the power of GNSS transmission signals, which carry almost exclusively vegetation information, as a priori information input to calibrate the influence of vegetation on the reflected signal from the soil surface to maximize the decoupling of the two reflected signals. Furthermore, signals from above- and below-vegetation GNSS antennas were simultaneously collected using a low-cost, dual-channel GNSS chipset, which can increase GNSS signal processing channels while reducing equipment costs. The results show that the solution proposed in this study can reach a correlation coefficient of 0.96 between the retrieval and in situ soil moisture content (SMC), and the root mean square error (RMSE) is reduced to 0.013 cm3/cm3. Moreover, the transmitted signal power, pseudorange STD, and carrier phase STD showed a clear trend with the vegetation growth status (VGS).