Tide variation monitoring based improved GNSS-MR by empirical mode decomposition

Global Navigation Satellite System multipath reflectometry (GNSS-MR) technology has great potential for monitoring tide level changes. GNSS-MR techniques usually extract signal-to-noise ratio (SNR) residual sequences using quadratic polynomials; however, such algorithms are affected considerably by satellite elevation angles. To improve the stability and accuracy of an SNR residual sequence, this study proposed an SNR signal decomposition method based on empirical mode decomposition (EMD). First, the SNR signal is decomposed by EMD, following which the SNR residual sequence is obtained by combining the corresponding intrinsic mode function with the frequency range of the coherent signal. Second, the Lomb–Scargle spectrum is analyzed to obtain the frequency of the SNR residual sequence. Finally, the SNR frequency is converted into the tide height. To verify the validity of the SNR residual sequence obtained by EMD, the algorithm performance was assessed using multigroup satellite elevation angle intervals with measured data from two station, SC02 in the United States and RSBY in Australia. Experimental results demonstrated that the accuracy of the improved algorithm was improved in the low-elevation range. The improved algorithm demonstrated high monitoring accuracy, and the effective number was not less than 80% of the total in SC02, which means it could effectively describe the trend of the tide with accuracy of approximately 10 cm, meanwhile, the RMS error of RSBY could be reduced by 30 cm, to the maximum extent. The EMD method effectively expands the range of available GNSS-MR elevations, avoids the loss of effective information, enhances considerably the utilization rate of GNSS data, and improves the accuracy of GNSS-MR tide level monitoring.