# Analysis of Key Issues on GNSS-R Soil Moisture Retrieval Based on Different Antenna Patterns
## 4 Conclusions  
Since the reflected signals from GNSS have begun to be used to obtain surface parameters through remote sensing, the GNSS-R technology has been gradually extended from sea surface remote sensing applications to land surface remote sensing applications. As an important branch of land surface remote sensing, soil moisture remote sensing via GNSS-R has formed two observation patterns  
Figure 11: Soil moisture estimation result of an aviation experiment with GNSS-R over Zhengzhou. (a) Distribution of soil moisture at the specular reflection point; (b) soil water grid data (at a resolution of 20 \(\times\) 20 m). Figure 12: Soil moisture detection depths histogram generated from an aviation experiment with GNSS-R in Zhengzhou. (single-antenna and multi-antenna patterns) along with their respective research methods. Currently, multiple low-orbit satellites equipped with a GNSS-R device have been launched to facilitate various in-flight observation programs worldwide. To improve the technical maturity of soil moisture remote sensing via GNSS-R and to promote its business applications, it is necessary to evaluate the accuracy of the soil moisture estimation. The keys to this evaluation are determining the geographic location of the specular reflection point, the spatial resolution and the soil detection depth. A feasible operational basis can be provided for evaluating the accuracy of GNSS-R soil moisture retrieval by clarifying these three key issues. In this study, an iterative method for determining the location of the specular reflection point is presented, and the effect of geoid and terrain height on the location of the specular reflection point is analyzed. Based on the discussion of the geometric characteristics of equi-delay ellipses of the reflected signal of GNSS, the concept of the resolution of GNSS remote sensing is introduced, and its mathematical formulas are presented. For smooth and rough ground, the spatial resolution algorithm is different. In reference to microwave remote sensing theory, the calculation formula of the penetration distance of GNSS signals in the soil is also presented, while the concepts of detection depth and penetration distance are distinguished. Using ground-based observation via the single-antenna pattern and air-based observation via the multi-antenna pattern as examples, this study analyzed three common key issues from the perspective of practical applications. For the single-antenna pattern, to provide a reference for the product use and accuracy evaluation, this study used the published PBO soil moisture product to present the relative location of the specular reflection point, the surface range and area of the reflected GPS signal, and the estimated detection depth represented by soil moisture in the time series. The interference signals which contains direct signals and ground reflection signals can be obtained from the signal noise ratio (SNR) data. After the analysis of the interference waveform, the direct signal can be removed and the sinusoidal waveform can be used for calculation. For the multi-antenna pattern, the structure can be regarded as a bistatic radar. In this study, using the air-based preliminary studies conducted, we quantitatively described the spatial distribution, the spatial resolution, and the detection depth of soil moisture via GNSS-R. Moreover, in terms of surface parameter remote sensing, the signal of the BeiDou satellite mainly differs from the GPS in the frequency of the band. Therefore, the analyses of the above common key problems are also applicable to remote sensing via the reflected signal of the BeiDou satellite. A quantitative reference was provided for the application of remote sensing using the reflected signal from the BeiDou satellite via the single-antenna pattern. Furthermore, future development will likely shift from air-based preliminary studies to satellite-based observation.