FengYun-3E (FY3E), launched on 5 July 2021, is one of China’s polar-orbiting meteorological satellite series. The GNOS II onboard FY3E is an operational GNSS remote sensor that for the first time combines GNSS radio occultation (GNSS RO) and GNSS reflectometry (GNSS-R). It has eight reflection channels that can track eight specular points at the same time, receiving reflected signals from multiple GNSS systems, including GPS, BeiDou and Galileo. The basic GNSS-R output generated by GNOS II is a 122 × 20 non-uniform delay-Doppler map whose high resolution portion captures more information near the specular point. This paper introduces the GNSS-R aspect of the FengYun-3E GNOS II, including the instrument, power calibration and wind speed retrieval algorithm. Preliminary validation results for its first four months of data are also presented. After preliminary quality control, the overall wind speed error is less than 2 m/s at wind speeds below 20 m/s for data from both GPS satellites and BeiDou satellites when compared to the ECMWF reanalysis winds.

The Global Navigation Satellite System Occultation Sounder II (GNOS-II) payload onboard the Chinese Fengyun-3E (FY-3E) satellite is the world’s first operational spaceborne mission that can utilize reflected signals from multiple navigation systems for Earth remote sensing. The satellite was launched into an 836-km early-morning polar orbit on 5 July 2021. Different GNSS signals show different characteristics in the observations and thus require different calibration methods. With an average data latency of less than 3 h, many near real-time applications are possible. This article first introduces the FY-3E/GNOS-II mission and instrument design, then describes the extensive calibration methods for the multi-GNSS measurements, and finally presents application results in the remote sensing of ocean surface winds, land soil moisture and sea ice extent. Especially, the ocean surface wind product has been used in operational applications such as assimilation in the numerical weather prediction model and monitoring of tropical cyclones. Currently, GNOS-II has been carried by FY-3E, FY-3F (launched in August 2023) and FY-3G (launched in April 2023). It will be also carried by future follow-on FY series and a more complete multi-GNSS reflectometry constellation will be established.

Two different Global Navigation Satellite System (GNSS) Reflectometry wind products are to be developed for the Global Navigation Satellite System Occultation Sounder II (GNOS-II) payload on the FengYun-3E (FY-3E) satellite: A global wind product optimized for global low-to-medium wind speeds and a cyclone wind product optimized for high wind speeds in the tropical and extratropical cyclones. This article presents a comprehensive assessment of the GNOS-II global wind product for both global positioning system (GPS) and Beidou (BDS) product at wind speeds below 25 m/s using its data of first six months. Three datasets, including the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis, HY-2B scatterometer and Soil Moisture Active Passive (SMAP) winds, are used for the assessment. The assessment of the Level 1 observables shows that the instrument's performance and calibration are generally stable. For the assessment of retrieved winds, the general performances of GPS and BDS products are similar. The overall wind speed root-mean-square error is 1.54 m/s for GPS-R and 1.44 m/s for BDS-R when compared with ECMWF, 1.48 m/s for GPS-R and 1.36 m/s for BDS-R when compared with HY-2B, and 2.08 m/s for GPS-R and 2.04 m/s for BDS-R when compared with SMAP. The overall wind speed biases for GPS-R and BDS-R are about zeros when compared with each dataset. The assessment is also made by the dependence on time, signal-to-noise ratio, observable, GNSS block, wind speed, incidence angle, and geography. Overall, the FY-3E GNOS-II global wind product is consistent over time and space with an accuracy meeting the requirement of operational use.

Soil moisture is the most active part of the terrestrial water cycle, and it is a key variable that affects hydrological, bio-ecological, and bio-geochemical processes. Microwave remote sensing is an effective means of monitoring soil moisture, but the existing conventional radiometers and single-station radars cannot meet the scientific needs in terms of temporal and spatial resolution. The emergence of GNSS-R (Global Navigation Satellite Systems Reflectometry) technology provides an alternative method with high temporal and spatial resolution. An important application field of GNSS-R is soil moisture monitoring, but it is still in the initial stage of research, and there are many uncertainties and open issues. Based on a review of the current state-of-the-art of soil moisture retrieval using GNSS-R, this paper points out the limitations of existing research in observation geometry, polarization, and coherent and non-coherent scattering. The smooth surface reflectivity model, the random rough surface scattering model, and the first-order radiation transfer equation model of the vegetation, which are in the form of bistatic and full polarization, are employed. Simulations and analyses of polarization, observation geometry (scattering zenith angle and scattering azimuth angle), Brewster angle, coherent and non-coherent component, surface roughness, and vegetation effects are carried out. The influence of the EIRP (Effective Isotropic Radiated Power) and the RFI (Radio Frequency Interference) on soil moisture retrieval is briefly discussed. Several important development directions for space-borne GNSS-R soil moisture retrieval are pointed out in detail based on the microwave scattering model.

This paper introduces the Chinese Tianmu-1 GNSS-R constellation of 22 small satellites launched in 2023–2024 and comprehensively evaluates the latest version of the in-orbit data. First, the mission design and instrument technology are described, which largely builds on the Fengyun-3/GNOS-II missions. Notable innovations include full-GNSS compatibility and dual-polarization antenna. Then, the spatiotemporal characteristics of the constellation are analyzed—specifically, coverage percentage and mean revisit time at different latitudes. Next, the accuracy of its science products including ocean surface winds and land soil moisture has been assessed, with two application cases demonstrating the mission’s utility for monitoring tropical cyclones and flooding. Finally, this paper for the first time evaluates Tianmu’s polarized observations including Horizontal (H), Vertical (V), Left-Hand Circularly-Polarized (LHCP) and Right-Hand Circularly-Polarized (RHCP). Analysis of the signal-to-noise ratio and reflectivity shows that the dual-polarimetric observations follow the trend of theoretical models and hold promise for advancing land remote sensing.

The reflected GNSS signals at the L-band is significantly advantageous in soil moisture monitoring as they are sensitive to the dielectric properties determined by the volumetric water content of topsoil, and they can penetrate vegetation, except in very dense forests. The Global Navigation satellite system Occultation Sounder (GNOS-II) with a reflectometry technique onboard the Fengyun-3E (FY-3E) satellite, launched on 5 July 2021, is the first mission that can receive reflected Global Navigation Satellite System (GNSS) signals from GPS, BeiDou and Galileo systems. This paper presents the soil moisture retrieval results from the FY-3E GNOS-II mission using 16 months of data. In this study, the reflectivity observations from different GNSS systems were firstly intercalibrated with some differences analyzed. Observations were also corrected by considering vegetation attenuation for 16 different land cover classifications. Finally, an empirical model was constructed for volumetric soil moisture (VSM) estimation, where the reflectivity of GNOS-II was linearly related to the SMAP reference soil moisture for each 36 km ease grid. The overall root-mean-square error of the retrieved soil moisture is 0.049 compared with the SMAP product, and 0.054 compared with the in situ data. The results of the three GNSS systems show similar levels of accuracy. This paper, for the first time, demonstrates the feasibility of global soil moisture retrieval using multiple GNSS signals.