TOWARDS REAL-TIME GNSS REFLECTOMETRY USING KALMAN FILTERING
Paper i proceeding, 2018
GNSS-R has emerged as an attractive way of using a signal of opportunity that is collected by GNSS stations all around the world to measure a wide variety of properties of the surroundings of the stations. Current state-of-the-art algorithms based on the inversion of SNR values rely on off-line processing, causing a significant delay before results are available. We present a new approach for ground-based GNSS-R that uses Kalman filtering with a realistic physical model that allows close to real-time inversion of SNR oscillations into sea-surface height with high precision. From the analysis of test measurements from the GTGU GNSS installation at the Onsala Space Observatory, Sweden, we conclude that the new method provides better estimates than single-arc retrievals from spectral analysis and that the final precision is close to that of post-processing inversion algorithms.