GNSS-IR Model of Sea Level Height Estimation Combining Variational Mode Decomposition

The Global Navigation Satellite System-Reflections (GNSS-R) signal has been confirmed to be used retrieve sea level height. At present, the GNSS-Interferometric Reflectometry (GNSS-IR) technology based on least square method process signal-to-noise ratio (SNR) data is restricted by satellite elevation angle in terms of accuracy and stability. This paper proposes a new GNSS-IR model combining variational mode decomposition (VMD) for height estimation. VMD decompose SNR into intrinsic functions (IMF) layers with different frequencies, remove IMF representing trend item data, reconstruct remaining components obtain oscillation item. In order verify validity model, measurement provided Onsala Space Observatory Sweden evaluate performance algorithm its stability high range. experimental results show that good stability, advantages compared other methods. For half-year GNSS root mean error (RMSE) correlation coefficient are 4.86 cm 0.97, respectively.