An Improved Tidal Current Separation Method of Radial Basis Function Using Gradient Training

Ship-mounted acoustic Doppler current profiler (ADCP) measurements have been used to obtain detailed observations of the spatial patterns of flows. To separate tidal and subtidal currents from the ship-mounted ADCP data at tidal reach, traditional harmonic analysis method require redundant measurements, and complex tidal current separation operations. Developments in radial basis function (RBF) interpolation theory are demonstrated to significantly improve the quality of the tidal velocity field extracted from the measurements. Tidal current separation method of RBF using greedy fit couldn't optimal centers for RBF, and the over-fitting of RBF would lead to the instability of separation model. To overcome these deficiencies, this paper proposes an improved tidal current separation method of radial basis function using gradient training. The tidal current separation results in Xuliujing section verified the feasibility of the tidal current separation method of gradient training RBF. The inner precision of reconstructed flow field based on the tidal current separation method using gradient training is better than 0.21 m/s, and the prediction accuracy is better than 0.25 m/s.