Spaceborne GNSS-R (global navigation satellite system reflectometry) is an innovative and powerful bistatic radar remote sensing technique that uses specialized GNSS-R instruments on LEO (low Earth orbit) satellites to receive GNSS L-band signals reflected by the Earth's surface. Unlike monostatic radar, the illuminated areas are elliptical regions centered on specular reflection points. Evaluation of the spatiotemporal resolution of the reflections is necessary at the GNSS-R mission design stage for various applications. However, not all specular reflection signals can be received because the size and location of the GNSS-R antenna's available reflecting ground coverage depends on parameters including the on-board receiver antenna gain, the signal frequency and power, the antenna face direction, and the LEO's altitude. Additionally, the number of available reflections is strongly related to the number of GNSS-R LEO and GNSS satellites. By 2020, the Galileo and BeiDou Navigation Satellite System (BDS) constellations are scheduled to be fully operational at global scale and nearly 120 multi-GNSS satellites, including Global Positioning System (GPS) and Global Navigation Satellite System (GLONASS) satellites, will be available for use as illuminators. In this paper, to evaluate the future capacity for repetitive GNSS-R observations, we propose a GNSS satellite selection method and simulate the orbit of eight-satellite LEO and partial multi-GNSS constellations. We then analyze the spatiotemporal distribution characteristics of the reflections in two cases: (1) When only GPS satellites are available; (2) when multi-GNSS satellites are available separately. Simulation and analysis results show that the multi-GNSS-R system has major advantages in terms of available satellite numbers and revisit times over the GPS-R system. Additionally, the spatial density of the specular reflections on the Earth's surface is related to the LEO inclination and constellation construction.

Abstract:Ground-based GNSS-R (global navigation satellite system reflectometry) can provide the absolute vertical distance from a GNSS antenna to the reflective surface of the ocean in a common height reference frame, given that vertical crustal motion at a GNSS station can be determined using direct GNSS signals. This technique offers the advantage of enabling ground-based sea level measurements to be more accurately determined compared with traditional tide gauges. Sea level changes can be retrieved from multipath effects on GNSS, which is caused by interference of the GNSS L-band microwave signals (directly from satellites) with reflections from the environment that occur before reaching the antenna. Most of the GNSS observation types, such as pseudo-range, carrier-phase and signal-to-noise ratio (SNR), suffer from this multipath effect. In this paper, sea level altimetry determinations are presented for the first time based on geometry-free linear combinations of the carrier phase at low elevation angles from a fixed global positioning system (GPS) station. The precision of the altimetry solutions are similar to those derived from GNSS SNR data. There are different types of observation and reflector height retrieval methods used in the data processing, and to analyze the performance of the different methods, five sea level determination strategies are adopted. The solutions from the five strategies are compared with tide gauge measurements near the GPS station, and the results show that sea level changes determined from GPS SNR and carrier phase combinations for the five strategies show good agreement (correlation coefficient of 0.97-0.98 and root-mean-square error values of <0.2 m).

High temporal and spatial resolutions are the key advantages of the global navigation satellites system-reflectometry (GNSS-R) technique, while low precision and instabilities constrain its development. Compared with conventional Ku/C band nadir-looking radar altimetry, the precision of GNSS-R code-level altimetry is restricted by the smaller bandwidth and the lower transmitted power of the signals. Fortunately, modernized GNSS broadcast new open-available ranging codes with wider bandwidth. The Chinese BDS-3 system was built on 31 July 2020; its inclined geostationary orbit and medium circular orbit satellites provide B1C and B2a public navigation service signals in the two frequency bands of B1 and B2. In order to investigate their performance on GNSS-R code-level altimetry, a coastal experiment was conducted on 5 November 2020 at a trestle of Weihai in the Shandong province of China. The raw intermediate frequency data with a 62 MHz sampling rate were collected and post-processed to solve the sea surface height every second continuously for over eight hours. The precisions were evaluated using the measurements from a 26 GHz radar altimeter mounted on the same trestle near our GNSS-R setup. The results show that a centimeter-level accuracy of GNSS-R altimetry—based on B1C code after the application of the moving average—can be achieved, while for B2a code, the accuracy is about 10 to 20 cm.

Flood is a kind of natural disaster that is extremely harmful and occurs frequently. To reduce losses caused by the hazards, it is urgent to monitor the disaster area timely and carry out rescue operations efficiently. However, conventional space observers cannot achieve sufficient spatiotemporal resolution. As spaceborne GNSS-R technique can observe the Earth’s surface with high temporal and spatial resolutions; and it is expected to provide a new solution to the problem of flood hazards. During 19–21 July 2021, Henan province, China, suffered a catastrophic flood and urban waterlogging. In order to test the feasibility of flood disaster monitoring on a daily basis by using GNSS-R observations, the CYGNSS (Cyclone Global Navigation Satellite System) Level 1 Science Data were processed for a few days before and after the flood to obtain surface reflectivity by correcting the analog power. Afterwards, the flood was monitored and mapped daily based on the analysis of changes in surface reflectivity from spaceborne GNSS-R mission. The results were evaluated based on the image from MODIS (Moderate Resolution Imaging Spectroradiometer) data, and compared with the observations of SMAP (Soil Moisture Active Passive) in the same period. The results show that the area with high CYGNSS reflectivity corresponds to the flooded area monitored by MODIS, and it is also in high agreement with SMAP. Moreover, CYGNSS can achieve more detailed mapping and quantification of the inundated area and the duration of the flood, respectively, in line with the specific situation of the flood. Thus, spaceborne GNSS-R technology can be used as a method to monitor floods with high temporal resolution.

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Global navigation satellite system-reflectometry (GNSS-R) has great potential to be a novel technique for altimetry, which can be used to derive sea surface heights (SSH). Shipborne altimetry is an important method to measure local SSH with high spatial resolution. In order to test the feasibility of shipborne dual-antenna GNSS-R reflector height retrieval, we developed a GNSS-R receiver system and performed experiments on a research vessel. In this study, direct and reflected GPS/BDS signals were collected using the same setup, and processed to estimate the reflector heights on the basis of path-delay measurements. A strategy of obtaining the GPS/BDS code-level path delay based on 10-ms coherent integration waveforms was adopted. We analyzed the relationship between the path-delay error and the error of the estimated reflector height, and we pointed out that the error in the path delay was amplified when the satellite elevation was low. We also performed reflector height retrieval based on BDS-3 signals for the first time. We evaluated the precisions of the BDS-R and GPS-R derived reflector heights with 30°and 50°cut-off elevations. The results show that the standard deviation of solutions at different cases is around 1.0 m and precisions are slightly better for a 50°cut-off angle compared with a 30°cut-off angle. In general, the mean values of different cases are close, with differences of several centimeters for the experiments.

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