Extraction and analysis of tidal level data based on time-frequency transformation

Extreme sea level phenomena are caused by tides, surges, and other factors, that pose potential threats to human settlements and ecosystems in coastal areas. Tidal level data is an important index for evaluating sea level change. Traditionally, the data are obtained through tidal stations, while modern measurement techniques are diversified with the development of global navigation satellite systems (GNSS). As a kind of navigation and monitoring equipment, offshore platforms combined with precise point positioning (PPP) technology can efficiently obtain high-precision tidal level data. However, there are signal disturbances in the offshore platform data that cannot be fully explained by natural phenomena, possibly due to GNSS technical issues. This study aims to preprocess and correct tidal level data by PPP technology, analyze the frequency components of tidal level data and their causes by using fast Fourier transform (FFT) and time-frequency transform, and provide support for studying the mechanism of sea level change.