## 1 Introduction
Subsequently, in 2018, they successfully applied altimetry to the Qinghai Lake water body using CYGNSS raw IF data, demonstrating the ability to measure inland water body altimetry using spaceborne GNSS-R raw IF data [24]. [PERSON] and [PERSON] [25] used a simulator to create raw IF data received by CYGNSS. This study differsfrom previous research in that it only tracked the carrier phase of the reflected signal, and the results showed that the relative phase can be used to calculate ice thickness. In subsequent studies, [PERSON] et al. (2022) evaluated sea surface altimetry using CYGNSS raw IF data and pointed out that using raw data can overcome the limitations of signal processing, data compression, and inaccurate or truncated delay variables in primary metadata. In 2020, [PERSON] et al. (2026) studied a height measurement method based on bistatic group delay using raw IF data received by TDS-1. The results showed that the model was consistent with the MSS model, and correcting GNSS-R satellite orbit errors through the MSS and least squares solutions could improve the deficiencies of level 1 data. This study provides a reference for using spaceborne GNSS-R raw IF data for height measurement. In 2021, [PERSON] and [PERSON] (2021) introduced an adaptive hybrid carrier tracking algorithm (AHT) suitable for processing coherent GNSS-R signals. AHT combines Doppler models with adaptive closed-loop (ACL) tracking, integrating master-slave open-loop (MS-OL) and closed-loop (CL) carrier-phase tracking systems, with a high accuracy and robustness, without the need for precise initialization. The article utilized CYGNSS raw IF data to study inland water, terrestrial, and open sea surfaces, demonstrating the excellent performance of AHT in these scenarios, especially in measuring ocean height, achieving centimeter-level high-precision ocean height measurement. In addition, AHT can also improve GNSS-R land applications and can be applied to tracking other wireless signals. [PERSON] et al. (2021) proposed a state-based method to address the issue of inaccurate measurement results caused by synchronous cyclic slip and noise filtering (SCANF) in dual-frequency GNSS-R phase measurements generated by OL tracking. This method can simultaneously handle cyclic slip and noise in OL tracking. At the same time, the performance of this method was demonstrated in the article by using real GNSS-R phase measurement values recorded by the receiver on the Spire low-Earth-orbit (LEO) satellite. The results showed that the average root mean square (RMS) of the sea surface height anomaly (SSHA) obtained by retrieval relative to the MSS was 7.3 cm. OL tracking is a common GNSS-R data processing method that is typically simpler than closed-loop tracking, but also more susceptible to noise and cyclic slip. The experimental results verified the effectiveness and superiority of the method, therefore, the proposal of this method is crucial for improving the effectiveness of OL tracking. In 2022, [PERSON] et al. (2022) explored the processing of raw IF data from multi-satellite GNSS-R missions and demonstrated the application of raw IF data in inland water detection and elevation measurement, providing new insights for the use of raw IF data in related fields. In addition, in reference ([PERSON] et al., 2021), the algorithm for detecting surface water in the upcoming HydroGNSS mission was tested using low-speed DDMs from NASA/CYGNSS and raw IF signals collected from CYGNSS and TDS-1. The test results met the 90% accuracy requirement of the mission, demonstrating the importance of studying raw IF data in the design and optimization of spaceborne GNSS-R instruments. With the continuous improvement and refinement of spaceborne GNSS-R raw IF signal processing technology and related algorithms, the application of spaceborne GNSS-R raw IF signals in inland water bodies, oceans, the ionosphere, the troposphere, and other related fields has great potential and plays a huge role in improving observation accuracy.