A Novel Sea Clutter Suppression Method based on Neural Network

In order to suppress sea clutter effectively, it is necessary to estimate the center and width of the power spectrum of sea clutter accurately. Since the complex property of sea clutter, traditional methods cannot estimate the accurate parameters of power spectrum of sea clutter, which leads to the decrease of the clutter suppression performance. In this paper, a sea clutter suppression method based on neural network is proposed, where the real sea clutter datasets are taken to train the neural network. Finally, real sea clutter data is input into neural network to estimate the center and width of the power spectrum. The results show that the neural network is more accurate in estimating the spectral center and width than the traditional method. Moreover, the filter designed by the proposed method has a better clutter suppression performance