## 1 Introduction
The ground receiver SMIGOL reflectometer was used to measure the instantaneous power that is from the interference of the direct and the reflected signal from the ground. Then, the soil moisture was determined by the position of the point (the notch point) where the amplitude fluctuation of the instantaneous power is the smallest. Another similar approach used GPS multipath reflection signals to perform soil content retrieval and is presented with only one antenna and a classical GNSS receiver [26; 27; 28]. A representative result [29] is from the University of Colorado, USA. The experiment used a right-hand circularly polarized antenna pointing to the sky and a GPS receiver featured with a geodetic characteristic to receive the direct signals and land-surface reflected signals that caused multipath effects. By measuring the signal-to-noise ratio of the received signal, soil moisture content can be obtained, and the method can be applied to sensing other different objects, such as inverted barometer and storm [30]. At present, various types of space-based, on-board observation experiments are vigorously carried out, and many countries are vigorously promoting related applications [31]. Following the launch of the UK-DMC satellite carrying GPS reflected signal receiving equipment in the UK in 2003 [32], the international exploration of GNSS-R spaceborne observations has developed rapidly. For example, the UK TDS-1 satellite launched in Kazakhstan in 2014 is equipped with SGR-ReSI (Space GNSS Receiver-Remote Sensing Instrument) sensors for GNSS-R measurements [33] are currently used for soil moisture inversion studies [34]. NASA has launched the CYGNSS observation constellation in December 2016. Especially, some significant results have been found utilizing space-borne data for the soil moisture content (SMC) application. For instance, the sensitivity of GNSS-R observables and SM was studied well in detail using TDS-1 data [35]. The sensitivity of the calibrated GNSS-R reflectivity to surface soil moisture was found to be ~0.09 dB/% at an incident angle of ~30\({}^{\circ}\) and decrease as the angle of incidence increased. In another study concerning the first global-scale assessment of GNSS-R, soil moisture active passive (SMAP) mission for soil moisture and biomass determination and scattering properties over land were evaluated and the results showed that the sensitivity to the effects of the Earth's topography and above ground biomass (ABG) was even over that of Amazonian and Boreal forests [36]. For the CYGNSS mission, the influence of the GNSS satellites' elevation angle on the reflectivity of LHCP, as a function of soil moisture content (SMC) and effective surface roughness parameter was revealed [37]. Also, the relationship between forward scattered L-band global navigation satellite system (GNSS) signals, recorded by the CYGNSS constellation and SMAP soil moisture (SM) was studied [38]. It showed the sensitivity of CYGNSS to SM that varies spatially and can be used to convert reflectivity to the estimates of SM. The unbiased root-mean-square difference between daily average CYGNSS-derived SM and SMAP SM is 0.045 cm\({}^{3}\)/cm\({}^{3}\) and is similarly low between CYGNSS and in situ SM. The development of space-borne sensors was greatly promoting the related study on a global scale. In the meanwhile, many empirical and electromagnetic bistatic models were evolved [39; 40; 41], enriching the knowledge of the scattering effects taking place in GNSS-R soil moisture retrieval. It is crucial to choose features that have the greatest impact on the results so as to reduce the number of variables when building a model, which is occasionally overlooked. Apart from that, most of the researches only focus on the studies of the soil moisture retrieval algorithm. Besides, the existing methods of soil moisture retrieval using GNSS-R technology are mostly based on analytical and semi-empirical models, which often need plenty of experimental data and are deficient in generalization ability.