Spatiotemporal Evaluation of GNSS-R Based on Future Fully Operational Global Multi-GNSS and Eight-LEO Constellations

Abstract

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.

On the Constellation Design of Multi-GNSS Reflectometry Mission Using the Particle Swarm Optimization Algorithm

“…More specifically, the average numbers of points fluctuated around the values of 40, 120, 300, and 600 for the optimal 8-, 24-, 60-, and 120-satellite 2D-LFCs, respectively. What needs to be mentioned is that Gao et al [15] simulated the distribution of the GNSS-R reflection points observed by a LEO constellation with main orbit parameters similar to CYGNSS and found that there is a peak of average numbers of reflection points at 120° E, which was attributed to the denser reflections to BDS GEO and IGSO satellites in the Asia-Pacific region, while in our work, this peak did not exist. This could be due to the fact that both the LEO constellation configurations and the settings for the selection of observable reflections were different between Gao et al's and our studies.…”

“…In the simulation, four steps were followed to determine the available reflected GNSS signals: (1) For each LEO satellite, the potentially available GNSS satellites for reflection observations were selected; (2) The positions of the specular reflection points could be calculated after the positions of the LEO and the GNSS satellites were determined; (3) As shown in Figure 1, only the specular points located within the minimum antenna gain could be contacted; and (4) Furthermore, only the locations of the specular points with 10 highest range corrected gain (RCG) were considered (see the detail of RCG in [16]). In addition, it should be mentioned that the LEO satellites were 3-axis stabilized and the antenna beam widths of the LEO satellites simulated in the present study were the same as that of the TDS-1 satellite, considering that the definitive beam widths of the CYGNSS mission have not been given [15].…”

“…Following Gao [15], the multi-GNSS signals from GPS, GLONASS, Galileo, and BDS were used as the signal sources for GNSS-R observations in the present simulation. What needs to be mentioned is that the four full operational GNSS constellations were all simulated based on their nominal constellation configurations presented in [24][25][26][27], considering that Galileo and BDS have not yet reached their full planned constellations until now, and the third generation of BDS was used.…”

“…The spatial distribution can be presented by the longitudinal and latitudinal distributions of the GNSS reflections. The temporal distribution is depicted using the mean revisit time, which is defined as the time interval between successive passes in one bin and is calculated by dividing the period with the number of continuous ground tracks on the Earth's surface formed by the reflections [15].…”

“…Zavorotny 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 Gao et al [15] and it was revealed that by considering the fusion of GPS, BDS, GLONASS, and Galileo, the spatio-temporal resolutions of GNSS reflections were improved substantially. Furthermore, Bussy-Virat et al [16] investigated the relationship between the spatial resolution and the temporal one of GNSS-R observations, and analyzed their dependence on key orbit parameters of the LEO satellites.…”