Gravity field recovery based on GNSS data of nano-satellites: a case study for the Spire CubeSat constellation

Abstract A growing number of Low Earth Orbiting (LEO) satellites are collecting GNSS tracking data that allows to recover the long-wavelength part of the Earth’s time-variable gravity field. Besides scientific LEO missions, commercial satellite constellations consisting of a huge number of nano-satellites are moving into focus. Due to an improved ground track coverage, such constellations offer the opportunity to increase the spatio-temporal resolution of derived gravity field models and can contribute to reduce temporal aliasing errors of dedicated gravity field missions. The Spire constellation is of particular interest as it consists of more than 100 nano-satellites (standardized CubeSats), all equipped with high-quality GNSS receivers. Furthermore, the Spire constellation offers a variety of orbital characteristics with different inclinations at altitudes of about 400–650 km. In this study, we use GNSS data from nine Spire CubeSats to derive monthly gravity field solutions covering a six-month period. The orbit and gravity field recovery is performed with the Bernese GNSS Software, which applies the Celestial Mechanics Approach. We demonstrate that the 2–3 times larger noise level of the Spire GNSS observations affects the quality of the retrieved gravity field solutions in the same order of magnitude. Therefore, a single Spire CubeSat solution cannot compete with those obtained from scientific LEO missions. However, with an increasing number of CubeSats, the performance improves so that a combination based on data from all nine Spire CubeSats can achieve a quality level comparable to a solution derived from ESA’s Swarm-B satellite.