Gerardo Allende-Alba, Peter Steigenberger, Institute of Communications and Navigation, German Aerospace Center (DLR); Steffen Thoelert, DLR - RWTH Aachen University

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Over the last few years, the number of applications with high reliability and integrity requirements of GNSS signals has grown exponentially. Such a demand has put into focus the implementation of monitoring systems that provide information about the GNSS signal quality. A key element in the navigation signal transmission chain is the satellite antenna, which is typically considered as a stable element with nominal performance during the life span of a given GNSS satellite. However, due to a diversity of factors, GNSS satellite antennas may exhibit a non-nominal on-orbit performance. In an effort to characterize the on-orbit performance of satellite navigation antennas, the present contribution proposes an analysis based on three key features: gain pattern, group delay variations map and phase center offset. For a given antenna under analysis, each of these features is reconstructed/estimated using observations available in common geodetic-grade GNSS receivers. In this contribution, the proposed methodology has been employed to characterize the on-orbit performance of the antennas of GLONASS satellites R719 and R720 based on recent analyses of signal power observations that suggest the occurrence of events on March 11, 2020 and April 4, 2019, respectively. The obtained comparisons of reconstructed gain patterns for both satellites before and after the mentioned days exhibit differences in specific pattern sectors at the 1-2 dB level. Likewise, the corresponding comparisons of reconstructed group delay variations maps for both satellites exhibit also differences in specific map regions at the 5-10 cm level for both cases. For the case of estimated phase center offsets, jumps of 10-15 cm are observed on the mentioned days. These findings provide a hint of the occurrence of events that change the nominal performance of GNSS satellite components, highlighting the importance of multi-feature analyses that may support monitoring systems for applications with high reliability and integrity requirements.