## 1 Introduction  
Over the past few decades, global navigation satellite systems (GNSSs) have been successfully applied for positioning, navigation, and timing as well as for Earth remote sensing. Particularly, GNSS-Reflectometry (GNSS-R) is an innovative remote sensing technique that uses the GNSS signals reflected from the Earth's surface to derive a variety of geophysical parameters [1; 2]. The application of GNSS reflectometry data for the ocean altimetry was first proposed by [PERSON] [3], and the global positioning system (GPS) reflected signals were used to sense the roughness of the reflecting surface, which was demonstrated by [PERSON] et al. [4]. At the same time, the first space-borne observation of an Earth-reflected GPS signal, which was obtained by the space shuttle spaceborne imaging radar-C (SIR-C) at an altitude of 200 km, was an initial measurement to scale GNSS-R measurements to obtain the expected signal-to-noise ratio (SNR) for estimating geophysical parameters [5]. Since then, several GNSS-R missions have been launched to verify the feasibility of this technique. The remote-sensing measurement using GPS reflection signals was later performed by the UK-Disaster Monitoring Constellation (UK-DMC) mission in 2004 [6]. A huge number of GNSS reflections have been acquired and further GNSS-R missions are inspired by this pioneering constellation, although the GPS reflections collected by this mission were not capable of demonstrating the robust capabilities of the GNSS-R technique as they are thinly dispersed [7; 8]. The TechDemoSat-1 (TDS-1) satellite launched in 2014, which carries a GNSS-R instrument, has provided a key demonstration of the capabilities of GNSS-R to derive high-quality ocean surface winds [9]. Following the great success achieved by TDS-1, the U.S. CYclone Global Navigation Satellite System (CYGNSS), the first GNSS-R constellation composed of eight micro-satellites orbiting at a 35\({}^{\circ}\) inclination and 520 km altitude, was launched on December 15, 2016, and each CYGNSS satellite can track up to four parallel reflected GPS L1 signals [10]. Although this constellation was originally designed to measure the ocean wind speed in hurricanes and tropical cyclones, the GNSS-R data collected by it also contributes to other geophysical applications such as the measurements of soil moisture over land and ice thickness [11; 12]. The development of different global navigation satellite systems including GPS, GLONASS, the Chinese BeiDou navigation system (BDS), and Galileo, have made the number of available satellites that can be used as platforms for GNSS-R signal sources increasing continuously in recent years, which gives potential for the use of multiple GNSS signals for GNSS-R. A Spanish experimental nanosatellite for both GNSS-R and GNSS Radio Occultation (RO) called \({}^{3}\)Cat-2 was successfully launched in 2016, and this experimental satellite investigated the feasibility of the use of multi-GNSS signals for GNSS-R in the future [13]. Higher spatial and temporal resolutions of GNSS reflections, as an important component for designing a GNSS-R system, is a motivation for extensive research. [PERSON] et al. [14] simulated six low Earth orbit (LEO) constellations for GNSS-R observations based on Walker constellation patterns and evaluated their performance for detecting six historic tsunami events. The results showed that the performance of the simulated constellation generally became better as the number of satellites and the orbit altitude increased. [PERSON] et al. [2] simulated a possible future GNSS-R constellation that consisted of 24 polar orbiting satellites, and the results demonstrate the global coverage of the GNSS-R observations provided by this constellation with an average revisit time of less than two hours over the globe. The potential performance of GNSS-R with four operational GNSS systems was first demonstrated by [PERSON] et al.