## 8 Summary and Future Prospects  
The raw IF signals in spaceborne GNSS-R has broad application prospects. This article summarizes the application status of this technology in multiple fields, including the launch status of spaceborne GNSS-R microsatellites, coherence detection, inland water detection, the surface height measurement of inland (or lake) water bodies, group delay sea surface height measurement, carrier-phase sea surface height measurement, ice height (or ice sheet height) retrieval, ionospheric total electron content and disturbance observations, and troposphere monitoring. These application studies demonstrate enormous potential in multiple fields for GNSS-R raw IF signal measurement technology. In addition to the applications in various fields mentioned above, researchers are also constantly exploring other applications. In the latest study, [PERSON] et al. [127] proposed a new GNSS-R cryosphere application, which proves the practicality of spaceborne GNSS-R in the remote sensing of ice shelf surface deformation and roughness. However, the raw IF signals of spaceborne GNSS-R are still in the early stages of research, and L1 data is still dominant in various fields of application. Compared with L1 data, raw IF data contains more information, which provides new ideas for our research. As early as 2022, in the study by [PERSON] et al. [22], it was mentioned that the Institute of Space Sciences (ICE-CSIC, IEEC) generated corresponding data products from raw IF datasets collected by different missions. The raw IF datasets collected by TDS-1, CYGNSS, BF-1 A/B, and SPIRE RO missions can be accessed by the ICE-CSIC/IEEC team. These data products are publicly available through a public open-data server to promote new research and explore the potential of GNSS-R in new geophysical applications and future satellite missions. However, so far, the number of satellites that can provide raw IF data for spaceborne GNSS-R is limited, and it is not possible to provide sufficient raw data sets for application in various fields of research. In the future, with the launch of more spaceborne GNSS-R satellites and the accumulation of more raw data, raw IF data will be applied in different fields and can provide higher-accuracy measurement results. Therefore, with the continuous development and improvement of technology, the future should focus on the following aspects. The accuracy of signal processing and reflection signal analysis should be further improved. Future research should focus on developing more advanced algorithms and technologies to improve the efficiency of signal processing and the accuracy of reflection signal analysis. The integration and collaborative application of other remote sensing technologies should be strengthened. Spaceborne GNSS-R can be combined with other remote sensing technologies, such as radar and optical remote sensing, to achieve multi-source data fusion and improve the comprehensiveness and diversity of Earth observations. Application areas should be expanded, especially in environmental monitoring, climate change research, and weather prediction. The high spatiotemporal resolution and global coverage of spaceborne GNSS-R give it enormous potential in these fields, and future research should focus on applications in these key areas. The commercialization and engineering development of spaceborne GNSS-R technology should be promoted. Applying technology to practical applications requires overcoming a series of engineering and commercialization challenges, including data processing, data transmission, and data application. With the development of GNSS, more GNSS satellites and civilian signals can be used for GNSS-R. The development of new spaceborne processing strategies can improve the observational performance of spaceborne GNSS-R. In the latest study, [PERSON] et al. [86] proposed a spaceborne GNSS-R signal processing method that significantly improves the signal-to-noise ratio of reflected signals by coherently combining GPS III L1C/A and L1C reflection signals.