Sea surface wind retrieval from GNSS delay-Doppler map using two-dimension least-squares fitting
In this paper, a novel method is presented to retrieve sea surface wind speed and direction by fitting the two-dimensional simulated GNSS-R DDMs to measured data. The signal scattering model of Z-V and the sea surface roughness model of Cox and Munk are employed for the DDM simulation, and an 18-second incoherent correlation is performed on the measured signal to reduce the noise level. Meanwhile, a variable step-size iteration as well as a fitting threshold are used to reduce the computational cost and error rate of the fitting procedure, respectively. Unlike previous methods, all the DDM points with normalized power higher than the threshold are used in the least-square fitting. An optimal fitting threshold is also proposed. To validate the proposed method, the retrieving results based on a dataset from the UK-DMC satellite are compared with the in-situ measurements provided by the National Data Buoy Center, and good correlation is observed between the two.