GNSS-MR Sea Level Height Inversion Based on CEEMDAN
Currently,global warming is evident,and sea level height is constantly showing an upward trend.How to quickly and accu-rately obtain the trend of sea level height changes is of great significance for the security of coastal areas.With the continuous develop-ment and maturity of Global Navigation Satellite System(GNSS)technology,GNSS Multipath Reflection Measurement(GNSS-MR)technology has become one of the important methods for inversing sea level height changes.However,due to various factors,there is a problem of signal mixing in the collected signals.Based on this,this paper proposes a method of using Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(CEEMDAN)to extract seawater signals in signal-to-noise ratio,which solves the impact of ground,ground object reflection signals,and noise signals.The experiment was conducted using a signal-to-noise ratio(SNR)se-quence selected from a measurement station at Friday Harbor in the United States.The results showed that after removing noise using the CEEMDAN method,the accuracy of component inversion was improved by 22.08%compared to the original sequence,and the correlation coefficient was increased by 5.32%,verifying the effectiveness of the proposed method.
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