On the retrieval of the specular reflection in GNSS carrier observations for ocean altimetry

This paper presents an altimetric method for ocean monitoring by remote sensing. It uses carrier observations of reflected GNSS signals. The method is illustrated in a simulation study and applied to a long term experiment yielding an ocean tide spectrum. The altimetric concept is based on residual observations of Doppler frequency. A linear relation between Doppler residuals f0 and height departures ΔHfrom the surface level is derived. In contrast to existing phase‐based methods which are constrained by smooth ocean conditions, the frequency‐based retrieval here described holds good for rougher ocean conditions. Two retrievals of Doppler residuals are distinguished: Tracking Retrieval and Spectral Retrieval. A simulation study investigates the performance of Spectral Retrieval for a rough ocean surface with a noise‐like sea level deviationξ(t). Simulation settings were adjusted to reflection events in coastal experiments with an elevation range of [5…15] deg. In this range Tracking Retrieval tolerates a surface standard deviation σξ < 5 cm, whereas Spectral Retrieval tolerates σξ ≤ 30 cm. These limits correspond to significant wave heights of 20 cm for Tracking Retrieval and 1.2 m for Spectral Retrieval. The simulation results are confirmed by applying the altimetric method to the experimental data. The recovery of continuous phase tracks in experimental data is onerous and Tracking Retrieval only works for a period of smooth ocean conditions (162 events). By contrast, Spectral Retrieval yields altimetric estimates throughout the whole experiment (2607 events). The altimetric time series extends over more than 60 days and results in a tide spectrum that resolves diurnal (K1) and semidiurnal (M2, S2) constituents. The formal precision for these estimates lies in the decimeter range. Key Points A continuous phase retrieval fails for typical ocean reflection events Sea level can be estimated by inversion of Doppler residuals Long altimetric time series can be used for detailed tide studies