Sea level estimation from SNR data of geodetic receivers using wavelet analysis

Abstract

Previous studies have proved that commercial, off-the-shelf, geodetic-quality Global Positioning System (GPS) receivers can monitor water level using multipath interferometric characteristics from the sea surface. A Lomb–Scargle periodogram (LSP) is typically used to extract the multipath frequency from the signal-to-noise ratio (SNR), which relates to the vertical distance between the antenna phase center and the reflecting surface, and subsequently, estimate sea levels. A wavelet transform can be used to analyze the time series with a nonstationary power at different frequencies, as can be the case for multipath signals. In addition, wavelet transform analysis estimates the local energy and instantaneous frequency of the signal at every epoch, which is beneficial for water-level estimation. Therefore, we attempt to extract the instantaneous multipath frequency using wavelet transform analysis for water leveling with a geodetic GPS receiver. This study analyzed SNR data of GPS L1C from three test sites: the Kachemak Bay site PBAY (AK, USA), the Friday Harbor site SC02 (WA, USA), and the Brest Harbor site BRST (France). These sites are located in different multipath environments, from a rural coastal area to a busy harbor, and they experience different tidal regimes. The results show that the wavelet analysis has potential for the retrieval of sea level heights. For measurement site PBAY the comparison of the results obtained by the wavelet and LSP analysis yield consistency within a few percent. At the other two sites, SC02 and BRST, the agreement is significantly lower.