Simulation and Analysis of GPS Multipath for the GEDI Experiment Onboard the International Space Station

Abstract

GPS observations are critical to both mission operations and scientific experiments on-board the International Space Station (ISS). However, it has long been recognized that this dynamic platform presents a complex, challenging viewing geometry for tracking GPS signals. Many researchers have investigated the ISS multipath environment using simulations and empirical data analysis [1,2,3,4]. The goal of our work is to create high fidelity predictions of GPS satellite visibility and systematic multipath observation errors resulting from interactions between the incident GPS signals and the ISS. GPS visibility and multipath modeling for receivers on-board the ISS presents a unique challenge due to the dynamic structure, extensive sky blockages, and large flat reflectors. This work builds upon the Colorado Center For Astrodynamics Research (CCAR) Advanced GNSS Multipath Model (AGMM) software to enable high fidelity multipath modeling for ISS applications. A high resolution, publicly available CAD model of the ISS structure is incorporated, including realistic orbital and attitude motion of the station, motion of solar panels and radiators. Candidate GPS receivers and antennas can be placed anywhere on the structure for analysis, including comparisons of performance with different tracking parameters and antenna patterns. A significant improvement in computational capability of the AGMM has been achieved with the integration of the open-source Physically Based Rendering Techniques (PBRT) API for modeling of signal ray paths and specular surface reflections. Additional tools for visualizing ray paths and reflections are developed and illustrated, enabling a deeper understanding of the environmental constraints and impacts. Quantitative methods for comparing simulated to observed multipath are introduced to effectively evaluate and ultimately validate the model predictions. This improved simulation has been applied to the Global Ecosystem Dynamics Investigation lidar (GEDI) GPS receiver case study for data gathered on-orbit in January 2019. GEDI is a lidar instrument which provides global measurements of forest vertical structures and is mounted to the Japanese Exposed Facility (JEM-EF). Specifically, GEDI is attached to the anti-velocity side of the JEM-EF. This location creates a non-trivial environment for the receiving antenna. Substantial sky-blockages caused by the JEM, truss, port solar panels, and radiator structures limit the satellites available for tracking and are significant sources of multipath reflections. Figure 1 shows a sky plot of the GEDI antenna bore-sight view. The AGMM software is able to simulate multipath for the GEDI receiver much faster than previously possible, creating a rich dataset from which model comparisons can be drawn. Realistic simulations of the ISS environment are created by incorporating ISS on-orbit position and velocity data, as well as solar panel and radiator rotation angles. Quantitative comparisons between on-orbit and simulated data are performed for satellite visibility statistics code multipath spectral content as well as code multipath magnitude. Simulated satellite visibility matches on-orbit satellite visibility on average 92% of the time for each satellite track present in the GEDI on-orbit data. Code multipath is extracted from the dual frequency receiver using the so-called ionosphere-free code minus carrier observable. The spectral content of oscillations in both simulated and observed multipath data is extracted using auto regressive (AR) techniques. Quantitative comparisons between the AR results show that the simulation performs at a statistically significant level when compared to randomized data. Simulated RMS Code multipath magnitude is within 30 cm of the observed magnitude for a majority of the simulated data. However, large differences between simulated and observed magnitudes are common and likely a result of poor knowledge of the ISS structural properties with regard to reflected L-band signals. This quantitative analysis helps validate the results of the AGMM model, showing utility for mission planning of future GNSS receiver installations on-board the ISS.